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On Cooperative Coevolution and Global Crossover (2024)
Journal Article
Bull, L., & Liu, H. (2024). On Cooperative Coevolution and Global Crossover. IEEE Transactions on Evolutionary Computation, 1-1. https://doi.org/10.1109/tevc.2024.3355776

Cooperative coevolutionary algorithms (CCEAs) divide a given problem in to a number of subproblems and use an evolutionary algorithm to solve each subproblem. This letter is concerned with the scenario under which a single fitness measure exists. By... Read More about On Cooperative Coevolution and Global Crossover.

Evolving multi-valued regulatory networks on tuneable fitness landscapes (2023)
Journal Article
Bull, L. (2023). Evolving multi-valued regulatory networks on tuneable fitness landscapes. Complex Systems -Champaign-, 32(3), 289-307. https://doi.org/10.25088/ComplexSystems.32.3.289

Random Boolean networks have been used widely to explore aspects of gene regulatory networks. As the name implies, traditionally the model has used a binary representation scheme. This paper uses a modified form of the model to systematically explore... Read More about Evolving multi-valued regulatory networks on tuneable fitness landscapes.

A systematic review of machine-learning solutions in anaerobic digestion (2023)
Journal Article
Rutland, H., You, J., Liu, H., Bull, L., & Reynolds, D. (2023). A systematic review of machine-learning solutions in anaerobic digestion. Bioengineering, 10(12), Article 1410. https://doi.org/10.3390/bioengineering10121410

The use of machine learning (ML) in anaerobic digestion (AD) is growing in popularity and improves the interpretation of complex system parameters for better operation and optimisation. This systematic literature review aims to explore how ML is curr... Read More about A systematic review of machine-learning solutions in anaerobic digestion.

A generalised dropout mechanism for distributed systems (2022)
Journal Article
Bull, L., & Liu, H. (2023). A generalised dropout mechanism for distributed systems. Artificial Life, 29(2), 146-152. https://doi.org/10.1162/artl_a_00393

This letter uses a modified form of the NK model introduced to explore aspects of distributed control. In particular, a previous result suggesting the use of dynamically formed subgroups within the overall system can be more effective than global con... Read More about A generalised dropout mechanism for distributed systems.

A haploid-diploid evolutionary algorithm optimizing nanoparticle based cancer treatments (2022)
Book Chapter
Tsompanas, M., Bull, L., Adamatzky, A., & Balaz, I. (2022). A haploid-diploid evolutionary algorithm optimizing nanoparticle based cancer treatments. In I. Balaz, & A. Adamatzky (Eds.), Cancer, Complexity, Computation (237-251). Springer. https://doi.org/10.1007/978-3-031-04379-6_10

This paper uses a recent explanation for the fundamental haploid-diploid lifecycle of eukaryotic organisms to present a new evolutionary algorithm that differs from all previous known work using diploid representations. A form of the Baldwin effect h... Read More about A haploid-diploid evolutionary algorithm optimizing nanoparticle based cancer treatments.

Nonbinary representations in the NK and NKCS models (2022)
Journal Article
Bull, L. (2022). Nonbinary representations in the NK and NKCS models. Complex Systems -Champaign-, 31(1), 87-101. https://doi.org/10.25088/ComplexSystems.31.1.87

The NK model has been used widely to explore aspects of natural evolution and complex systems. Traditionally, the model has used a binary representation scheme. This paper introduces a modified form of the NK model through which to systematically exp... Read More about Nonbinary representations in the NK and NKCS models.

Evolving Boolean regulatory networks with variable gene expression times (2021)
Book Chapter
Bull, L. (2021). Evolving Boolean regulatory networks with variable gene expression times. In Handbook of Unconventional Computing (247-259). World Scientific Publishing. https://doi.org/10.1142/9789811235726_0007

The time taken for gene expression varies not least because proteins vary in length considerably. This paper uses an abstract, tuneable Boolean regulatory network model to explore gene expression time variation. In particular, it is shown how non-uni... Read More about Evolving Boolean regulatory networks with variable gene expression times.

Evolutionary algorithms designing nanoparticle cancer treatments with multiple particle types (2021)
Journal Article
Tsompanas, M. A., Bull, L., Adamatzky, A., & Balaz, I. (2021). Evolutionary algorithms designing nanoparticle cancer treatments with multiple particle types. IEEE Computational Intelligence Magazine, 16(4), 85-99. https://doi.org/10.1109/MCI.2021.3108306

There is a rich history of evolutionary algorithms tackling optimization problems where the most appropriate size of solutions, namely the genome length, is unclear a priori. Here, we investigated the applicability of this methodology on the problem... Read More about Evolutionary algorithms designing nanoparticle cancer treatments with multiple particle types.

On coevolution: Asymmetry in the NKCS model (2021)
Journal Article
Bull, L. (2021). On coevolution: Asymmetry in the NKCS model. BioSystems, 207, Article 104469. https://doi.org/10.1016/j.biosystems.2021.104469

The NKCS model was introduced to explore coevolutionary systems, that is, systems in which multiple species are closely interconnected. The fitness landscapes of the species are coupled to a controllable amount, where the underlying properties of the... Read More about On coevolution: Asymmetry in the NKCS model.

On the emergence of intersexual selection: Arbitrary trait preference improves female-male coevolution (2021)
Journal Article
Bull, L. (2021). On the emergence of intersexual selection: Arbitrary trait preference improves female-male coevolution. Artificial Life, 27(1), 15-25. https://doi.org/10.1162/artl_a_00335

Sexual selection is a fundamental aspect of evolution for all eukaryotic organisms with mating types. This article suggests intersexual selection is best viewed as a mechanism with which to compensate for the unavoidable dynamics of coevolution betwe... Read More about On the emergence of intersexual selection: Arbitrary trait preference improves female-male coevolution.

Autoencoding with a classifier system (2021)
Journal Article
Preen, R. J., Wilson, S. W., & Bull, L. (2021). Autoencoding with a classifier system. IEEE Transactions on Evolutionary Computation, 25(6), 1079 - 1090. https://doi.org/10.1109/TEVC.2021.3079320

Autoencoders are data-specific compression algorithms learned automatically from examples. The predominant approach has been to construct single large global models that cover the domain. However, training and evaluating models of increasing size com... Read More about Autoencoding with a classifier system.

Are artificial dendrites useful in neuro-evolution? (2021)
Journal Article
Bull, L. (2022). Are artificial dendrites useful in neuro-evolution?. Artificial Life, 27(2), 75-79. https://doi.org/10.1162/artl_a_00338

The significant role of dendritic processing within neuronal networks has become increasingly clear. This letter explores the effects of including a simple dendrite-inspired mechanism into neuro-evolution. The phenomenon of separate dendrite activati... Read More about Are artificial dendrites useful in neuro-evolution?.

Metameric representations on optimization of nano particle cancer treatment (2021)
Journal Article
Tsompanas, M. A., Bull, L., Adamatzky, A., & Balaz, I. (2021). Metameric representations on optimization of nano particle cancer treatment. Biocybernetics and Biomedical Engineering, 41(2), 352-361. https://doi.org/10.1016/j.bbe.2021.02.002

In silico evolutionary optimization of cancer treatment based on multiple nano-particle (NP) assisted drug delivery systems was investigated in this study. The use of multiple types of NPs is expected to increase the robustness of the treatment, due... Read More about Metameric representations on optimization of nano particle cancer treatment.

In silico optimization of cancer therapies with multiple types of nanoparticles applied at different times (2020)
Journal Article
Tsompanas, M. A., Bull, L., Adamatzky, A., & Balaz, I. (2020). In silico optimization of cancer therapies with multiple types of nanoparticles applied at different times. Computer Methods and Programs in Biomedicine, 200, Article 105886. https://doi.org/10.1016/j.cmpb.2020.105886

© 2020 The Author(s) Background and Objective: Cancer tumors constitute a complicated environment for conventional anti-cancer treatments to confront, so solutions with higher complexity and, thus, robustness to diverse conditions are required. Alter... Read More about In silico optimization of cancer therapies with multiple types of nanoparticles applied at different times.

Novelty search employed into the development of cancer treatment simulations (2020)
Journal Article
Tsompanas, M., Bull, L., Adamatzky, A., & Balaz, I. (2020). Novelty search employed into the development of cancer treatment simulations. Informatics in Medicine Unlocked, 19, 100347. https://doi.org/10.1016/j.imu.2020.100347

Conventional optimization methodologies may be hindered when the automated search is stuck into local optima because of a deceptive objective function landscape. Consequently, open ended search methodologies, such as novelty search, have been propose... Read More about Novelty search employed into the development of cancer treatment simulations.

Exploring distributed control with the NK model (2020)
Journal Article
Bull, L. (2020). Exploring distributed control with the NK model. International Journal of Parallel, Emergent and Distributed Systems, 35(4), 413-422. https://doi.org/10.1080/17445760.2020.1760864

The NK model has been used widely to explore aspects of natural evolution and complex systems. This paper introduces a modified form of the NK model for exploring distributed control in complex systems such as organisations, social networks, collecti... Read More about Exploring distributed control with the NK model.

Towards an evolvable cancer treatment simulator (2019)
Journal Article
Preen, R. J., Bull, L., & Adamatzky, A. (2019). Towards an evolvable cancer treatment simulator. BioSystems, 182, 1-7. https://doi.org/10.1016/j.biosystems.2019.05.005

© 2019 Elsevier B.V. The use of high-fidelity computational simulations promises to enable high-throughput hypothesis testing and optimisation of cancer therapies. However, increasing realism comes at the cost of increasing computational requirements... Read More about Towards an evolvable cancer treatment simulator.

Design mining microbial fuel cell cascades (2018)
Journal Article
Preen, R., You, J., Bull, L., & Ieropoulos, I. A. (2019). Design mining microbial fuel cell cascades. Soft Computing, 23(13), 4673-7643. https://doi.org/10.1007/s00500-018-3117-x

Microbial fuel cells (MFCs) perform wastewater treatment and electricity production through the conversion of organic matter using microorganisms. For practical applications, it has been suggested that greater efficiency can be achieved by arranging... Read More about Design mining microbial fuel cell cascades.

The evolution of sex through the Baldwin effect (2017)
Journal Article
Bull, L. (2017). The evolution of sex through the Baldwin effect. Artificial Life, 23(4), 481-492. https://doi.org/10.1162/ARTL_a_00242

This paper suggests that the fundamental haploid-diploid cycle of eukaryotic sex exploits a rudimentary form of the Baldwin effect. With this explanation for the basic cycle, the other associated phenomena can be explained as evolution tuning the amo... Read More about The evolution of sex through the Baldwin effect.

On Design Mining: Coevolution and Surrogate Models (2017)
Journal Article
Preen, R., & Bull, L. (2017). On Design Mining: Coevolution and Surrogate Models. Artificial Life, 23(2), 186-205. https://doi.org/10.1162/ARTL_a_00225

© 2017 Massachusetts Institute of Technology. Published under a Creative Commons Attribution 3.0 Unported (CC BY 3.0) license. Design mining is the use of computational intelligence techniques to iteratively search and model the attribute space of ph... Read More about On Design Mining: Coevolution and Surrogate Models.

Haploid-diploid evolutionary algorithms: The Baldwin effect and recombination nature’s way (2017)
Presentation / Conference
Bull, L. (2017, April). Haploid-diploid evolutionary algorithms: The Baldwin effect and recombination nature’s way. Paper presented at 2017 AISB Convention, Bath, UK

This paper uses the recent idea that the fundamental haploid-diploid lifecycle of eukaryotic organisms implements a rudimentary form of learning within evolution. A general approach for evolutionary computation is here derived that differs from all p... Read More about Haploid-diploid evolutionary algorithms: The Baldwin effect and recombination nature’s way.

3D printed components of microbial fuel cells: Towards monolithic microbial fuel cell fabrication using additive layer manufacturing (2016)
Journal Article
Preen, R. J., You, J., Preen, R., Bull, L., Greenman, J., & Ieropoulos, I. (2017). 3D printed components of microbial fuel cells: Towards monolithic microbial fuel cell fabrication using additive layer manufacturing. Sustainable Energy Technologies and Assessments, 19, 94-101. https://doi.org/10.1016/j.seta.2016.11.006

© 2016 The Authors For practical applications of the MFC technology, the design as well as the processes of manufacturing and assembly, should be optimised for the specific target use. Another burgeoning technology, additive manufacturing (3D printin... Read More about 3D printed components of microbial fuel cells: Towards monolithic microbial fuel cell fabrication using additive layer manufacturing.

Design mining interacting wind turbines (2016)
Journal Article
Preen, R. J., Preen, R., & Bull, L. (2016). Design mining interacting wind turbines. Evolutionary Computation, 24(1), 89-111. https://doi.org/10.1162/EVCO_a_00144

© 2016 by the Massachusetts Institute of Technology. An initial study has recently been presented of surrogate-assisted evolutionary algorithms used to design vertical-axis wind turbines wherein candidate prototypes are evaluated under fan-generated... Read More about Design mining interacting wind turbines.

Towards a Physarum learning chip (2016)
Journal Article
Whiting, J. G. H., Jones, J., Bull, L., Levin, M., & Adamatzky, A. (2016). Towards a Physarum learning chip. Scientific Reports, 6, Article 19948. https://doi.org/10.1038/srep19948

Networks of protoplasmic tubes of organism Physarum polycehpalum are macro-scale structures which optimally span multiple food sources to avoid repellents yet maximize coverage of attractants. When data are presented by configurations of attractants... Read More about Towards a Physarum learning chip.

Evolving unipolar memristor spiking neural networks (2015)
Journal Article
Howard, G. D., Bull, L., & De Lacy Costello, B. (2015). Evolving unipolar memristor spiking neural networks. Connection Science, 27(4), 397-416. https://doi.org/10.1080/09540091.2015.1080225

© 2015 Taylor & Francis. Neuromorphic computing – brain-like computing in hardware – typically requires myriad complimentary metal oxide semiconductor spiking neurons interconnected by a dense mesh of nanoscale plastic synapses. Memristors are freq... Read More about Evolving unipolar memristor spiking neural networks.

A brief history of learning classifier systems: from CS-1 to XCS and its variants (2015)
Journal Article
Bull, L. (2015). A brief history of learning classifier systems: from CS-1 to XCS and its variants. Evolutionary Intelligence, 8(2-3), 55-70. https://doi.org/10.1007/s12065-015-0125-y

© 2015, Springer-Verlag Berlin Heidelberg. The direction set by Wilson’s XCS is that modern Learning Classifier Systems can be characterized by their use of rule accuracy as the utility metric for the search algorithm(s) discovering useful rules. Suc... Read More about A brief history of learning classifier systems: from CS-1 to XCS and its variants.

On the evolution of Boolean networks for computation: A guide RNA mechanism (2015)
Journal Article
Bull, L. (2016). On the evolution of Boolean networks for computation: A guide RNA mechanism. International Journal of Parallel, Emergent and Distributed Systems, 31(2), 101-113. https://doi.org/10.1080/17445760.2015.1057590

© 2015 Taylor & Francis. There is a growing body of work within computational intelligence which explores the use of representations inspired by the genetic regulatory networks of biological cells. This paper uses a recently presented abstract, tun... Read More about On the evolution of Boolean networks for computation: A guide RNA mechanism.

A Cognitive Architecture Based on a Learning Classifier System with Spiking Classifiers (2015)
Journal Article
Howard, D., Howard, G. D., Bull, L., & Lanzi, P. L. (2016). A Cognitive Architecture Based on a Learning Classifier System with Spiking Classifiers. Neural Processing Letters, 44(1), 125-147. https://doi.org/10.1007/s11063-015-9451-4

© 2015, Springer Science+Business Media New York. Learning classifier systems (LCS) are population-based reinforcement learners that were originally designed to model various cognitive phenomena. This paper presents an explicitly cognitive LCS by usi... Read More about A Cognitive Architecture Based on a Learning Classifier System with Spiking Classifiers.

On the evolution of behaviors through embodied imitation (2015)
Journal Article
Erbas, M. D., Bull, L., & Winfield, A. F. (2015). On the evolution of behaviors through embodied imitation. Artificial Life, 21(2), 141-165. https://doi.org/10.1162/ARTL_a_00164

© 2015 Massachusetts Institute of Technology. Abstract This article describes research in which embodied imitation and behavioral adaptation are investigated in collective robotics. We model social learning in artificial agents with real robots. The... Read More about On the evolution of behaviors through embodied imitation.

Towards the evolution of vertical-axis wind turbines using supershapes (2014)
Journal Article
Preen, R., & Bull, L. (2014). Towards the evolution of vertical-axis wind turbines using supershapes. Evolutionary Intelligence, 7(3), 155-167. https://doi.org/10.1007/s12065-014-0116-4

© 2014, Springer-Verlag Berlin Heidelberg. We have recently presented an initial study of evolutionary algorithms used to design vertical-axis wind turbines (VAWTs) wherein candidate prototypes are evaluated under fan generated wind conditions after... Read More about Towards the evolution of vertical-axis wind turbines using supershapes.

Toward the Coevolution of Novel Vertical-Axis Wind Turbines (2014)
Journal Article
Preen, R., & Bull, L. (2015). Toward the Coevolution of Novel Vertical-Axis Wind Turbines. IEEE Transactions on Evolutionary Computation, 19(2), 284-294. https://doi.org/10.1109/TEVC.2014.2316199

© 1997-2012 IEEE. The production of renewable and sustainable energy is one of the most important challenges currently facing mankind. Wind has made an increasing contribution to the world's energy supply mix, but remains a long way from reaching its... Read More about Toward the Coevolution of Novel Vertical-Axis Wind Turbines.

Evolving spiking networks with variable resistive memories (2014)
Journal Article
Howard, G., Bull, L., de Lacy Costello, B., Gale, E., & Adamatzky, A. (2014). Evolving spiking networks with variable resistive memories. Evolutionary Computation, 22(1), 79-103. https://doi.org/10.1162/EVCO_a_00103

Neuromorphic computing is a brainlike information processing paradigm that requires adaptive learning mechanisms. A spiking neuro-evolutionary system is used for this purpose; plastic resistive memories are implemented as synapses in spiking neural n... Read More about Evolving spiking networks with variable resistive memories.

Evolving Boolean regulatory networks with epigenetic control (2014)
Journal Article
Bull, L. (2014). Evolving Boolean regulatory networks with epigenetic control. BioSystems, 116(1), 36-42. https://doi.org/10.1016/j.biosystems.2013.12.004

The significant role of epigenetic mechanisms within natural systems has become increasingly clear. This paper uses a recently presented abstract, tunable Boolean genetic regulatory network model to explore aspects of epigenetics. It is shown how dyn... Read More about Evolving Boolean regulatory networks with epigenetic control.

Evolving functional and structural dynamism in coupled boolean networks (2014)
Journal Article
Bull, L. (2014). Evolving functional and structural dynamism in coupled boolean networks. Artificial Life, 20(4), 441-455. https://doi.org/10.1162/ARTL_a_00137

© 2014 Massachusetts Institute of Technology. This article uses a recently presented abstract, tunable Boolean regulatory network model to further explore aspects of mobile DNA, such as transposons. The significant role of mobile DNA in the evolution... Read More about Evolving functional and structural dynamism in coupled boolean networks.

Towards the evolution of novel vertical-axis wind turbines (2013)
Presentation / Conference
Preen, R., & Bull, L. (2013, September). Towards the evolution of novel vertical-axis wind turbines. Paper presented at 13th UK Workshop on Computational Intelligence, UKCI 2013, Guildford, UK

Renewable and sustainable energy is one of the most important challenges currently facing mankind. Wind has made an increasing contribution to the world's energy supply mix, but still remains a long way from reaching its full potential. In this paper... Read More about Towards the evolution of novel vertical-axis wind turbines.

Embodied imitation-enhanced reinforcement learning in multi-agent systems (2013)
Journal Article
Erbas, M. D., Winfield, A. F., & Bull, L. (2014). Embodied imitation-enhanced reinforcement learning in multi-agent systems. Adaptive Behavior, 22(1), 31-50. https://doi.org/10.1177/1059712313500503

Imitation is an example of social learning in which an individual observes and copies another's actions. This paper presents a new method for using imitation as a way of enhancing the learning speed of individual agents that employ a well-known reinf... Read More about Embodied imitation-enhanced reinforcement learning in multi-agent systems.

Discrete and fuzzy dynamical genetic programming in the XCSF learning classifier system (2013)
Journal Article
Preen, R., & Bull, L. (2014). Discrete and fuzzy dynamical genetic programming in the XCSF learning classifier system. Soft Computing, 18(1), 153-167. https://doi.org/10.1007/s00500-013-1044-4

A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to neural networks. This paper presents results from an investigation into using discrete and fuzzy dynamical system repr... Read More about Discrete and fuzzy dynamical genetic programming in the XCSF learning classifier system.

Dynamical genetic programming in XCSF (2013)
Journal Article
Preen, R. J., Preen, R., & Bull, L. (2013). Dynamical genetic programming in XCSF. Evolutionary Computation, 21(3), 361-387. https://doi.org/10.1162/EVCO_a_00080

A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to artificial neural networks. This paper presents results from an investigation into using a temporally dynamic symbolic... Read More about Dynamical genetic programming in XCSF.

Imitation programming unorganised machines (2013)
Book Chapter
Bull, L. (2013). Imitation programming unorganised machines. In X. Yang (Ed.), Artificial Intelligence, Evolutionary Computing and Metaheuristics: in the Footsteps of Alan Turing (63-81). Springer

In 1948 Alan Turing presented a general representation scheme by which to achieve artificial intelligence – his unorganised machines. Further, at the same time as also suggesting that natural evolution may provide inspiration for search, he noted tha... Read More about Imitation programming unorganised machines.

Toward turing’s A-type unorganised machines in an unconventional substrate: A dynamic representation in compartmentalised excitable chemical media (2013)
Book Chapter
Bull, L., Holley, J., De Lacy Costello, B., & Adamatzky, A. (2013). Toward turing’s A-type unorganised machines in an unconventional substrate: A dynamic representation in compartmentalised excitable chemical media. . Springer. https://doi.org/10.1007/978-3-642-37225-4_11

© Springer-Verlag Berlin Heidelberg 2013. Turing presented a general representation scheme by which to achieve artificial intelligence – unorganised machines. Significantly, these were a form of discrete dynamical system and yet such representations... Read More about Toward turing’s A-type unorganised machines in an unconventional substrate: A dynamic representation in compartmentalised excitable chemical media.

Evolving boolean networks on tunable fitness landscapes (2012)
Journal Article
Bull, L. (2012). Evolving boolean networks on tunable fitness landscapes. IEEE Transactions on Evolutionary Computation, 16(6), 817-828. https://doi.org/10.1109/TEVC.2011.2173578

This paper presents an abstract, tunable model by which to explore aspects of artificial genetic regulatory networks and their design by simulated evolution. The random Boolean network formalism is combined with the NK and $NKCS$ models of fitness la... Read More about Evolving boolean networks on tunable fitness landscapes.

Evolution of plastic learning in spiking networks via memristive connections (2012)
Journal Article
Howard, G., Howard, D., Gale, E., Bull, L., De Lacy Costello, B., & Adamatzky, A. (2012). Evolution of plastic learning in spiking networks via memristive connections. IEEE Transactions on Evolutionary Computation, 16(5), 711-729. https://doi.org/10.1109/TEVC.2011.2170199

This paper presents a spiking neuroevolutionary system which implements memristors as plastic connections, i.e., whose weights can vary during a trial. The evolutionary design process exploits parameter self-adaptation and variable topologies, allowi... Read More about Evolution of plastic learning in spiking networks via memristive connections.

Creating unorganised machines from memristors (2012)
Presentation / Conference
Howard, G. D., Bull, L., Costello, B. D. L., & Adamatzky, A. (2012, September). Creating unorganised machines from memristors. Paper presented at ICNAAM 2012: International Conference of Numerical Analysis and Applied Mathematics, Kos, Greece

On architectures of circuits implemented in simulated Belousov-Zhabotinsky droplets (2012)
Journal Article
Adamatzky, A., Holley, J., Dittrich, P., Gorecki, J., De Lacy Costello, B., Zauner, K. P., & Bull, L. (2012). On architectures of circuits implemented in simulated Belousov-Zhabotinsky droplets. BioSystems, 109(1), 72-77. https://doi.org/10.1016/j.biosystems.2011.12.007

When lipid vesicles filled with Belousov-Zhabotinsky (BZ) excitable chemical medium are packed in tight assembles, waves of excitation may travel between the vesicles. When several waves meet in a vesicle some fragments may deflect, others can annihi... Read More about On architectures of circuits implemented in simulated Belousov-Zhabotinsky droplets.

Production system rules as protein complexes from genetic regulatory networks: An initial study (2012)
Journal Article
Bull, L. (2012). Production system rules as protein complexes from genetic regulatory networks: An initial study. Evolutionary Intelligence, 5(2), 59-67. https://doi.org/10.1007/s12065-012-0078-3

This short paper introduces a new way by which to design production system rules. An indirect encoding scheme is presented which views such rules as protein complexes produced by the temporal behaviour of an artificial genetic regulatory network. Thi... Read More about Production system rules as protein complexes from genetic regulatory networks: An initial study.

Evolution of supershapes for the generation of three-dimensional designs (2012)
Journal Article
Preen, R. J., & Bull, L. (2012). Evolution of supershapes for the generation of three-dimensional designs

This paper explores the evolution of three-dimensional objects with a simple generative encoding, known as the Superformula. Evolving three-dimensional objects has long been of interest in a wide array of disciplines, from engineering (e.g., robotics... Read More about Evolution of supershapes for the generation of three-dimensional designs.

Cartesian genetic programming for memristive logic circuits (2012)
Journal Article
Howard, G. D., Bull, L., & Adamatzky, A. (2012). Cartesian genetic programming for memristive logic circuits. Lecture Notes in Artificial Intelligence, 7244 LNCS, 37-48. https://doi.org/10.1007/978-3-642-29139-5_4

In this paper memristive logic circuits are evolved using Cartesian Genetic Programming. Graphs comprised of implication logic (IMP) nodes are compared to more ubiquitous NAND circuitry on a number of logic circuit problems and a robotic control task... Read More about Cartesian genetic programming for memristive logic circuits.

Using genetical and cultural search to design unorganised machines (2012)
Journal Article
Bull, L. (2012). Using genetical and cultural search to design unorganised machines. Evolutionary Intelligence, 5(1), 23-33. https://doi.org/10.1007/s12065-011-0061-4

In 1948 Turing presented a general representation scheme by which to achieve artificial intelligence-his unorganised machines. Significantly, these were a form of discrete dynamical system and yet dynamical representations remain almost unexplored wi... Read More about Using genetical and cultural search to design unorganised machines.

On natural genetic engineering: structural dynamism in random boolean networks (2012)
Journal Article
Bull, L. (2012). On natural genetic engineering: structural dynamism in random boolean networks

This short paper presents an abstract, tunable model of genomic structural change within the cell lifecycle and explores its use with simulated evolution. A well-known Boolean model of genetic regulatory networks is extended to include changes in nod... Read More about On natural genetic engineering: structural dynamism in random boolean networks.

Evolving boolean networks with structural dynamism (2012)
Journal Article
Bull, L. (2012). Evolving boolean networks with structural dynamism. Artificial Life, 18(4), 385-397. https://doi.org/10.1162/ARTL_a_00073

This short article presents an abstract, tunable model of genomic structural change within the cell life cycle and explores its use with simulated evolution. A well-known Boolean model of genetic regulatory networks is extended to include changes in... Read More about Evolving boolean networks with structural dynamism.

A simple computational cell: Coupling boolean gene and protein networks (2012)
Journal Article
Bull, L. (2012). A simple computational cell: Coupling boolean gene and protein networks. Artificial Life, 18(2), 223-236

This article presents an abstract, tunable model containing two of the principal information-processing features of cells and explores its use with simulated evolution. The random Boolean model of genetic regulatory networks is extended to include a... Read More about A simple computational cell: Coupling boolean gene and protein networks.

Logical and arithmetic circuits in Belousov-Zhabotinsky encapsulated disks (2011)
Journal Article
Holley, J., Jahan, I., De Lacy Costello, B., Bull, L., & Adamatzky, A. (2011). Logical and arithmetic circuits in Belousov-Zhabotinsky encapsulated disks. Physical Review E, 84(5), 056110. https://doi.org/10.1103/PhysRevE.84.056110

Excitation waves on a subexcitable Belousov-Zhabotinsky (BZ) substrate can be manipulated by chemical variations in the substrate and by interactions with other waves. Symbolic assignment and interpretation of wave dynamics can be used to perform log... Read More about Logical and arithmetic circuits in Belousov-Zhabotinsky encapsulated disks.

On computing in fine-grained compartmentalised Belousov-Zhabotinsky medium (2011)
Journal Article
Adamatzky, A., Holley, J., Bull, L., & De Lacy Costello, B. (2011). On computing in fine-grained compartmentalised Belousov-Zhabotinsky medium. Chaos, Solitons and Fractals, 44(10), 779-790. https://doi.org/10.1016/j.chaos.2011.03.010

We introduce results of computer experiments on information processing in a hexagonal array of vesicles filled with Belousov-Zhabotinsky (BZ) solution in a sub-excitable mode. We represent values of Boolean variables by excitation wave-fragments and... Read More about On computing in fine-grained compartmentalised Belousov-Zhabotinsky medium.

Fuzzy dynamical genetic programming in XCSF (2011)
Conference Proceeding
Preen, R., & Bull, L. (2011). Fuzzy dynamical genetic programming in XCSF. In N. Krasnogor, & P. L. Lanzi (Eds.), Proceedings of the 13th annual conference companion on Genetic and evolutionary computation. , (167-168). https://doi.org/10.1145/2001858.2001952

A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to Neural Networks, and more recently Dynamical Genetic Programming (DGP). This paper presents results from an investigat... Read More about Fuzzy dynamical genetic programming in XCSF.

Towards a mapping of modern AIS and LCS (2011)
Journal Article
Bull, L. (2011). Towards a mapping of modern AIS and LCS. Lecture Notes in Artificial Intelligence, 6825 LNCS, 371-382. https://doi.org/10.1007/978-3-642-22371-6_32

For many years correlations between aspects of Artificial Immune Systems (AIS) and Learning Classifier Systems (LCS) have been highlighted. However, neither field appears to have benefitted from such work not least since the differences between the t... Read More about Towards a mapping of modern AIS and LCS.

Vesicle computers: Approximating a Voronoi diagram using Voronoi automata (2011)
Journal Article
Adamatzky, A., De Lacy Costello, B., Holley, J., Gorecki, J., & Bull, L. (2011). Vesicle computers: Approximating a Voronoi diagram using Voronoi automata. Chaos, Solitons and Fractals, 44(7), 480-489. https://doi.org/10.1016/j.chaos.2011.01.016

Irregular arrangements of vesicles filled with excitable and precipitating chemical systems are imitated by Voronoi automata - finite-state machines defined on a planar Voronoi diagram. Every Voronoi cell takes four states: resting, excited, refracto... Read More about Vesicle computers: Approximating a Voronoi diagram using Voronoi automata.

Evolving spiking networks with variable memristors (2011)
Presentation / Conference
Howard, G. D., Gale, E., Bull, L., de Lacy Costello, B., & Adamatzky, A. (2011, June). Evolving spiking networks with variable memristors. Paper presented at 13th annual conference on Genetic and evolutionary computation

Arithmetic dynamical genetic programming in the XCSF learning classifier system (2011)
Presentation / Conference
Preen, R., & Bull, L. (2011, June). Arithmetic dynamical genetic programming in the XCSF learning classifier system. Paper presented at IEEE Congress on Evolutionary Computation (CEC), 2011, New Orleans, US

This paper presents results from an investigation into using a continuous-valued dynamical system representation within the XCSF Learning Classifier System. In particular, dynamical arithmetic genetic networks are used to represent the traditional... Read More about Arithmetic dynamical genetic programming in the XCSF learning classifier system.

Towards evolving spiking networks with memristive synapses (2011)
Presentation / Conference
Howard, G. D., Gale, E., Bull, L., de Lacy Costello, B., & Adamatzky, A. (2011, April). Towards evolving spiking networks with memristive synapses. Paper presented at IEEE Symposium on Artificial Life (ALIFE), 2011, Paris, France

This paper presents a spiking neuro-evolutionary system which implements memristors as neuromodulatory connections, ie whose weights can vary during a trial. The evolutionary design process exploits parameter self-adaptation and a constructionist app... Read More about Towards evolving spiking networks with memristive synapses.

Applications of Kauffman’s coevolutionary NKCS model to management and organization studies (2011)
Book Chapter
Vidgen, R., & Bull, L. (2011). Applications of Kauffman’s coevolutionary NKCS model to management and organization studies. In P. Allen, S. Maguire, & B. McKelvey (Eds.), The Sage Handbook of Complexity and Management (201-219). SAGE Publications Limited

A number of studies have used tuneable, abstract models of organism evolution like Kauffman's (1993) NK model to capture and explore aspects of organizations and their adaptation in the business environment (eg Levinthal, 1997; Rivkin, 2000; Lenox... Read More about Applications of Kauffman’s coevolutionary NKCS model to management and organization studies.

Computational modalities of Belousov-Zhabotinsky encapsulated vesicles (2011)
Journal Article
Holley, J., Adamatzky, A., Bull, L., De Lacy Costello, B., & Jahan, I. (2011). Computational modalities of Belousov-Zhabotinsky encapsulated vesicles. Nano Communication Networks, 2(1), 50-61. https://doi.org/10.1016/j.nancom.2011.02.002

We present both simulated and partial empirical evidences for the computational utility of many connected vesicle analogues of an encapsulated nonlinear chemical processing medium. By connecting small vesicles containing a solution of sub-excitable B... Read More about Computational modalities of Belousov-Zhabotinsky encapsulated vesicles.

On polymorphic logical gates in subexcitable chemical medium (2011)
Journal Article
Adamatzky, A., De Lacy Costello, B., & Bull, L. (2011). On polymorphic logical gates in subexcitable chemical medium. International Journal of Bifurcation and Chaos, 21(07), 1977-1986. https://doi.org/10.1142/S0218127411029574

In a subexcitable light-sensitive Belousov-Zhabotinsky (BZ) chemical medium an asymmetric disturbance causes the formation of localized traveling wave-fragments. Under the right conditions these wave-fragments can conserve their shape and velocity ve... Read More about On polymorphic logical gates in subexcitable chemical medium.

Towards arithmetic circuits in sub-excitable chemical media (2011)
Journal Article
Adamatzky, A., De Lacy Costello, B., Bull, L., & Holley, J. (2011). Towards arithmetic circuits in sub-excitable chemical media. Israel Journal of Chemistry, 51(1), 56-66. https://doi.org/10.1002/ijch.201000046

A sub-excitable Belousov-Zhabotinsky medium exhibits localized travelling excitations (in contrast to an excitable medium exhibiting target or spiral waves). Initially assymetric perturbations give birth to excitation wave-fragments. The shape and ve... Read More about Towards arithmetic circuits in sub-excitable chemical media.

A spiking neural representation for XCSF (2010)
Conference Proceeding
Lanzi, P. L., Howard, G., Howard, D., & Bull, L. (2010). A spiking neural representation for XCSF. https://doi.org/10.1109/CEC.2010.5586035

This paper presents a Learning Classifier System (LCS) where each traditional rule is represented by a spiking neural network, a type of network with dynamic internal state. The evolutionary design process exploits parameter self-adaptation and a con... Read More about A spiking neural representation for XCSF.

Artificial symbiogenesis and differing reproduction rates (2010)
Journal Article
Bull, L. (2010). Artificial symbiogenesis and differing reproduction rates. Artificial Life, 16(1), 65-72. https://doi.org/10.1162/artl.2009.16.1.16102

Symbiosis is the phenomenon in which organisms of different species live together in close association. Symbiogenesis is the name given to the process by which symbiotic partners combine and unify. This letter reconsiders previous work using the NKCS... Read More about Artificial symbiogenesis and differing reproduction rates.

Use of a connection-selection scheme in neural XCSF (2010)
Journal Article
Howard, G. D., Bull, L., & Lanzi, P. L. (2010). Use of a connection-selection scheme in neural XCSF. Lecture Notes in Artificial Intelligence, 6471 LNAI, 87-106. https://doi.org/10.1007/978-3-642-17508-4_7

XCSF is a modern form of Learning Classifier System (LCS) that has proven successful in a number of problem domains. In this paper we exploit the modular nature of XCSF to include a number of extensions, namely a neural classifier representation, sel... Read More about Use of a connection-selection scheme in neural XCSF.

Stochastic automated search methods in cellular automata: The discovery of tens of thousands of glider guns (2010)
Journal Article
Sapin, E., Adamatzky, A., Collet, P., & Bull, L. (2010). Stochastic automated search methods in cellular automata: The discovery of tens of thousands of glider guns. Natural Computing, 9(3), 513-543. https://doi.org/10.1007/s11047-009-9109-0

This paper deals with the spontaneous emergence of glider guns in cellular automata. An evolutionary search for glider guns with different parameters is described and other search techniques are also presented to provide a benchmark. We demonstrate t... Read More about Stochastic automated search methods in cellular automata: The discovery of tens of thousands of glider guns.

Index permutations and classes of additive cellular automata rules with isomorphic STD (2010)
Journal Article
Bulitko, V., Voorhees, B., Alonso-Sanz, R., Bull, L., Anghelescu, P., Ionita, S., …Jin, W. (2010). Index permutations and classes of additive cellular automata rules with isomorphic STD. Journal of Cellular Automata, 5(1-2), 1-28

First we consider the question of identifying linear transformations that transform any additive CA rule into an additive CA rule with an isomorphic STD. A general condition is derived. Following on this, we consider a subclass of such transformation... Read More about Index permutations and classes of additive cellular automata rules with isomorphic STD.

Parallel data mining-case study (2010)
Report
Tekiner, F., Pettipher, M., Bull, L., Studley, M., Whittley, I., & Bagnall, T. (2010). Parallel data mining-case study

On dynamical genetic programming: Simple Boolean networks in learning classifier systems (2009)
Journal Article
Bull, L. (2009). On dynamical genetic programming: Simple Boolean networks in learning classifier systems. International Journal of Parallel, Emergent and Distributed Systems, 24(5), 421-442. https://doi.org/10.1080/17445760802660387

Many representations have been presented to enable the effective evolution of computer programs. Turing was perhaps the first to present a general scheme by which to achieve this end. Significantly, Turing proposed a form of discrete dynamical system... Read More about On dynamical genetic programming: Simple Boolean networks in learning classifier systems.

Genetic approaches to search for computing patterns in cellular automata (2009)
Journal Article
Sapin, E., Bull, L., & Adamatzky, A. (2009). Genetic approaches to search for computing patterns in cellular automata. IEEE Computational Intelligence Magazine, 4(3), 20-28. https://doi.org/10.1109/MCI.2009.933097

The emergence of collision based computing in complex systems with local interactions is discussed. Simulations of logic gates have been inspired by the simulation of an AND gate by the Game of Life. The evolutionary algorithm is also used to modify... Read More about Genetic approaches to search for computing patterns in cellular automata.

Computer music meets unconventional computing: Towards sound synthesis with in vitro neuronal networks (2009)
Journal Article
Miranda, E. R., Bull, L., Gueguen, F., & Uroukov, I. S. (2009). Computer music meets unconventional computing: Towards sound synthesis with in vitro neuronal networks. Computer Music Journal, 33(1), 9-18. https://doi.org/10.1162/comj.2009.33.1.9

The feasibility of synthesizing sounds with hybrid wetware-silicon devices has been explored with the use of in vitro neuronal networks. The basics of culturing brain cells has been introduced while the procedures that has been established to stimula... Read More about Computer music meets unconventional computing: Towards sound synthesis with in vitro neuronal networks.

Experimental validation of binary collisions between wave fragments in the photosensitive Belousov–Zhabotinsky reaction (2009)
Journal Article
Toth, R., Stone, C., Adamatzky, A., de Lacy Costello, B., & Bull, L. (2009). Experimental validation of binary collisions between wave fragments in the photosensitive Belousov–Zhabotinsky reaction. Chaos, Solitons and Fractals, 41(4), 1605-1615. https://doi.org/10.1016/j.chaos.2008.07.001

Using the examples of an excitable chemical system (the Belousov–Zhabotinsky medium) and plasmodium of Physarum polycephalum we show that universal computation in a geometrically unconstrained medium is only possible when resources (excitability or c... Read More about Experimental validation of binary collisions between wave fragments in the photosensitive Belousov–Zhabotinsky reaction.

Experimental validation of binary collisions between wave fragments in the photosensitive Belousov-Zhabotinsky reaction (2009)
Journal Article
Toth, R., Stone, C., Adamatzky, A., de Lacy Costello, B., & Bull, L. (2009). Experimental validation of binary collisions between wave fragments in the photosensitive Belousov-Zhabotinsky reaction. Chaos, Solitons and Fractals, 41(4), 1605-1615. https://doi.org/10.1016/j.chaos.2008.07.001

We present experimental verification of wave fragment collisions in the sub-excitable Belousov-Zhabotinsky medium observed previously in simulation [Adamatzky A, De Lacy Costello B. Binary collisions between wave fragments in a sub-excitable Belousov... Read More about Experimental validation of binary collisions between wave fragments in the photosensitive Belousov-Zhabotinsky reaction.

Evolution of cellular automata with memory: The Density Classification Task (2009)
Journal Article
Stone, C., & Bull, L. (2009). Evolution of cellular automata with memory: The Density Classification Task. BioSystems, 97(2), 108-116. https://doi.org/10.1016/j.biosystems.2009.05.001

The Density Classification Task is a well known test problem for two-state discrete dynamical systems. For many years researchers have used a variety of evolutionary computation approaches to evolve solutions to this problem. In this paper, we invest... Read More about Evolution of cellular automata with memory: The Density Classification Task.

On dynamical genetic programming: Random boolean networks in learning classifier systems (2009)
Journal Article
Bull, L., & Preen, R. (2009). On dynamical genetic programming: Random boolean networks in learning classifier systems. Lecture Notes in Artificial Intelligence, 5481 LNCS, 37-48. https://doi.org/10.1007/978-3-642-01181-8_4

Many representations have been presented to enable the effective evolution of computer programs. Turing was perhaps the first to present a general scheme by which to achieve this end. Significantly, Turing proposed a form of discrete dynamical system... Read More about On dynamical genetic programming: Random boolean networks in learning classifier systems.

Discrete dynamical genetic programming in XCS (2009)
Presentation / Conference
Preen, R., & Bull, L. (2009, July). Discrete dynamical genetic programming in XCS. Paper presented at 11th Annual conference on Genetic and evolutionary computation, Montreal, Canada

A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results from an investigation into using a discrete dynamical system representati... Read More about Discrete dynamical genetic programming in XCS.

Spiral formation and degeneration in heterogeneous excitable media (2009)
Journal Article
Toth, R., De Lacy Costello, B., Stone, C., Masere, J., Adamatzky, A., & Bull, L. (2009). Spiral formation and degeneration in heterogeneous excitable media. Physical Review E, 79(3), 035101(R) (4 pages). https://doi.org/10.1103/PhysRevE.79.035101

Spontaneous spiral formation occurs when an excitation wave is input to a heterogeneous network of low- and high-light-intensity cells projected onto a light-sensitive Belousov-Zhabotinsky reaction. The range of network conditions where spirals form... Read More about Spiral formation and degeneration in heterogeneous excitable media.

Implementation of glider guns in the light-sensitive Belousov-Zhabotinsky medium (2009)
Journal Article
De Lacy Costello, B., Toth, R., Stone, C., Adamatzky, A., & Bull, L. (2009). Implementation of glider guns in the light-sensitive Belousov-Zhabotinsky medium. Physical Review E, 79(2), 026114. https://doi.org/10.1103/PhysRevE.79.026114

In cellular automata models a glider gun is an oscillating pattern of nonquiescent states that periodically emits traveling localizations (gliders). The glider streams can be combined to construct functionally complete systems of logical gates and th... Read More about Implementation of glider guns in the light-sensitive Belousov-Zhabotinsky medium.

On minimally coupled boolean networks (2009)
Journal Article
Alonso-Sanz, R., & Bull, L. (2009). On minimally coupled boolean networks. International Journal of Bifurcation and Chaos, 19(04), 1401-1414. https://doi.org/10.1142/S0218127409023743

Traditional Boolean networks consist of nodes within a single network, each updating synchronously, although asynchronous versions have also been presented. In this paper the dynamics of two, mutually coupled traditional networks are investigated. In... Read More about On minimally coupled boolean networks.

Configuring ZCS for continuous-valued single-step Boolean problems (2009)
Journal Article
Stone, C., & Bull, L. (2009). Configuring ZCS for continuous-valued single-step Boolean problems. Analysis, 2(3), 19

In this paper we investigate the performance and operation of a Learning Classifier System on problems with real-valued states and a Boolean action space. Specifically, we study aspects of the algorithm and parameter set of the simple strength-based... Read More about Configuring ZCS for continuous-valued single-step Boolean problems.

Phase clustering in globally coupled photochemical oscillators (2008)
Journal Article
Taylor, A. F., Kapetanopoulos, P., Whitaker, B. J., Toth, R., Bull, L., & Tinsley, M. R. (2008). Phase clustering in globally coupled photochemical oscillators. European Physical Journal - Special Topics, 165(1), 137-149. https://doi.org/10.1140/epjst/e2008-00857-9

We experimentally investigate the formation of clusters in a population of globally coupled photochemical oscillators. The system consists of catalytic micro-particles in Belousov-Zhabotinsky solution and the coupling exploits the excitatory properti... Read More about Phase clustering in globally coupled photochemical oscillators.

Dynamic control and information processing in the Belousov-Zhabotinsky reaction using a coevolutionary algorithm (2008)
Journal Article
Toth, R., Stone, C., Adamatzky, A., De Lacy Costello, B., & Bull, L. (2008). Dynamic control and information processing in the Belousov-Zhabotinsky reaction using a coevolutionary algorithm. Journal of Chemical Physics, 129(18), 184708. https://doi.org/10.1063/1.2932252

We propose that the behavior of nonlinear media can be controlled dynamically through coevolutionary systems. In this study, a light-sensitive subexcitable Belousov-Zhabotinsky reaction is controlled using a heterogeneous cellular automaton. A checke... Read More about Dynamic control and information processing in the Belousov-Zhabotinsky reaction using a coevolutionary algorithm.

Coevolving cellular automata with memory for chemical computing: Boolean logic gates in the BZ reaction (2008)
Book Chapter
Stone, C., Toth, R., de Lacy Costello, B., Bull, L., & Adamatzky, A. (2008). Coevolving cellular automata with memory for chemical computing: Boolean logic gates in the BZ reaction. In G. Rudolph, T. Jansen, S. M. Lucas, C. Poloni, & N. Beume (Eds.), Parallel Problem Solving from Nature - PPSN X: 10th International Conference Dortmund, Germany, September 13-17, 2008 (579-588). Berlin/Heidelberg: Springer

Learning classifier systems in data mining: An introduction (2008)
Journal Article
Bernadó-Mansilla, E., Bull, L., & Holmes, J. (2008). Learning classifier systems in data mining: An introduction. Studies in Computational Intelligence, 125, 1-15. https://doi.org/10.1007/978-3-540-78979-6_1

This chapter provides an introduction to Learning Classifier Systems before reviewing a number of historical uses in data mining. An overview of the rest of the volume is then presented. © 2008 Springer-Verlag Berlin Heidelberg.

Foreign exchange trading using a learning classifier system (2008)
Journal Article
Stone, C., & Bull, L. (2008). Foreign exchange trading using a learning classifier system. Studies in Computational Intelligence, 125, 169-189. https://doi.org/10.1007/978-3-540-78979-6_8

We apply a simple Learning Classifier System to a foreign exchange trading problem. The performance of the Learning Classifier System is compared to that of a Genetic Programming approach from the literature. The simple Learning Classifier System is... Read More about Foreign exchange trading using a learning classifier system.

On the effect of long-term electrical stimulation on three-dimensional cell cultures: Hen embryo brain spheroids (2008)
Journal Article
Uroukov, I. S., & Bull, L. (2008). On the effect of long-term electrical stimulation on three-dimensional cell cultures: Hen embryo brain spheroids. Medical Devices: Evidence and Research, 1, 1-12. https://doi.org/10.2147/mder.s3245

A comprehensive dataset of multielectrode array recordings was collected from three-dimensional hen embryo brain cell cultures, termed spheroids, under long-term electrical stimulation. The aim is to understand the ongoing changes in the spiking acti... Read More about On the effect of long-term electrical stimulation on three-dimensional cell cultures: Hen embryo brain spheroids.

On coupling random boolean networks (2008)
Presentation / Conference
Bull, L., & Alonso-Sanz, A. (2008, June). On coupling random boolean networks. Paper presented at Automata 2008: Theory and Applications of Cellular Automata, Bristol, UK, Bristol, UK

Self-adaptive constructivism in neural xcs and xcsf (2008)
Presentation / Conference
Howard, D., Bull, L., & Lanzi, P. L. (2008, June). Self-adaptive constructivism in neural xcs and xcsf. Paper presented at 2008 Genetic and Evolutionary Computation Conference

Evolving localizations in reaction-diffusion cellular automata (2008)
Journal Article
Adamatzky, A., Bull, L., Collet, P., & Sapin, E. (2008). Evolving localizations in reaction-diffusion cellular automata. International Journal of Modern Physics C, 19(04), 557-567. https://doi.org/10.1142/S0129183108012376

We consider hexagonal cellular automata with immediate cell neighbourhood and three cell-states. Every cell calculates its next state depending on the integral representation of states in its neighbourhood, i.e., how many neighbours are in each one s... Read More about Evolving localizations in reaction-diffusion cellular automata.

Towards unconventional computing through simulated evolution: Control of nonlinear media by a learning classifier system (2008)
Journal Article
Bull, L., Budd, A., Stone, C., Uroukov, I., Costello, B. D. L., & Adamatzky, A. (2008). Towards unconventional computing through simulated evolution: Control of nonlinear media by a learning classifier system. Artificial Life, 14(2), 203-222. https://doi.org/10.1162/artl.2008.14.2.203

We propose that the behavior of nonlinear media can be controlled automatically through evolutionary learning. By extension, forms of unconventional computing (viz., massively parallel nonlinear computers) can be realized by such an approach. In this... Read More about Towards unconventional computing through simulated evolution: Control of nonlinear media by a learning classifier system.

Random number generation by cellular automata with memory (2008)
Journal Article
Alonso-Sanz, R., & Bull, L. (2008). Random number generation by cellular automata with memory. International Journal of Modern Physics C, 19(02), 351-367. https://doi.org/10.1142/S012918310801211X

This paper considers an extension to the standard framework of cellular automata which implements memory capabilities by featuring cells by elementary rules of its last three states. A study is made of the potential value of elementary cellular autom... Read More about Random number generation by cellular automata with memory.

Initial results from the use of evolutionary learning to control chemical computers (2008)
Journal Article
Budd, A., Stone, C., Masere, J., Adamatzky, A., de Lacy Costello, B., & Bull, L. (2008). Initial results from the use of evolutionary learning to control chemical computers. International Journal of Unconventional Computing, 4(1), 13-22

The behaviour of pulses of Belousov-Zhabotinski (BZ) reaction diffusion waves can be controlled automatically through machine learning. By extension, a form of chemical network computing, i.e., a massively parallel non-linear Computer, can be realise... Read More about Initial results from the use of evolutionary learning to control chemical computers.

Towards neuronal computing: simple creation of two logic functions in 3D cell cultures using multi-electrode arrays (2008)
Journal Article
Bull, L., & Uroukov, I. (2008). Towards neuronal computing: simple creation of two logic functions in 3D cell cultures using multi-electrode arrays. International Journal of Unconventional Computing, 4(2), 143-154

In this paper we begin by reviewing a number of previously presented approaches to control the electrical stimulation of in vitro neuronal networks for computation through the use of multi-electrode array technology. Drawing upon this research we des... Read More about Towards neuronal computing: simple creation of two logic functions in 3D cell cultures using multi-electrode arrays.

Boolean networks with memory (2008)
Journal Article
Alonso-Sanz, R., & Bull, L. (2008). Boolean networks with memory. International Journal of Bifurcation and Chaos, 18(12), 3799-3814. https://doi.org/10.1142/S0218127408022755

In standard Boolean Networks (BN) the new state of a cell depends upon the neighborhood configuration only at the preceding time step. The effect of implementing memory of different types in cells of BN with different degrees of random rewiring is st... Read More about Boolean networks with memory.

On lookahead and latent learning in simple LCS (2008)
Conference Proceeding
Bull, L. (2008). On lookahead and latent learning in simple LCS. https://doi.org/10.1007/978-3-540-88138-4_9

Learning Classifier Systems use evolutionary algorithms to facilitate rule- discovery, where rule fitness is traditionally payoff based and assigned under a sharing scheme. Most current research has shifted to the use of an accuracy-based scheme wher... Read More about On lookahead and latent learning in simple LCS.

Non-linear media based computers: chemical and neuronal networks through machine learning (2008)
Report
Bull, L., Adamatzky, A., de Lacy Costello, B., Husbands, P., O’Shea, M., Purcell, W., & Taylor, A. (2008). Non-linear media based computers: chemical and neuronal networks through machine learning

There is growing interest in research into the development of hybrid wetware-silicon devices focused on exploiting their potential for 'non-linear computing'. The aim is to harness the as yet only partially understood intricate dynamics of non-linear... Read More about Non-linear media based computers: chemical and neuronal networks through machine learning.

Knowledge discovery from medical data: an empirical study with XCS (2008)
Book Chapter
Kharbat, F., Odeh, M., & Bull, L. (2008). Knowledge discovery from medical data: an empirical study with XCS. In L. Bull, E. Bernado-Mansilla, & J. Holmes (Eds.), Learning Classifier Systems in Data Mining. Springer

In this chapter we describe the use of a modern learning classifier system to a data mining task. In particular, in collaboration with a medical specialist, we apply XCS to a primary breast cancer data set. Our results indicate more effective knowled... Read More about Knowledge discovery from medical data: an empirical study with XCS.

Towards clustering with learning classifier systems (2008)
Book Chapter
Tamee, K., Bull, L., & Pinngern, O. (2008). Towards clustering with learning classifier systems. In L. Bull, E. Bernadó-Mansilla, & J. Holmes (Eds.), Learning classifier systems in data mining (191-204). Springer

Using the XCS classifier system for multi-objective reinforcement learning problems (2007)
Journal Article
Studley, M., & Bull, L. (2007). Using the XCS classifier system for multi-objective reinforcement learning problems. Artificial Life, 13(1), 69-86. https://doi.org/10.1162/artl.2007.13.1.69

We investigate the performance of a learning classifier system in some simple multi-objective, multi-step maze problems, using both random and biased action-selection policies for exploration. Results show that the choice of action-selection policy c... Read More about Using the XCS classifier system for multi-objective reinforcement learning problems.

Anticipation mappings for learning classifier systems (2007)
Presentation / Conference
Bull, L., O'Hara, T., & Lanzi, P. L. (2007, September). Anticipation mappings for learning classifier systems. Paper presented at Evolutionary Computation, 2007. CEC 2007. IEEE Congress on, Singapore

Accuracy-based learning classifier system ensembles with rule-sharing (2007)
Journal Article
Bull, L., Studley, M., Bagnall, A., & Whittley, I. (2007). Accuracy-based learning classifier system ensembles with rule-sharing. IEEE Transactions on Evolutionary Computation, 11(4), 496-502. https://doi.org/10.1109/TEVC.2006.885163

Learning Classifier Systems (LCS) are a method of evolving compact rule-sets using reinforcement learning. This paper presents an investigation into exploiting the population-based nature of LCS for their use within highly-parallel systems, such as... Read More about Accuracy-based learning classifier system ensembles with rule-sharing.

Toward a better understanding of rule initialisation and deletion (2007)
Conference Proceeding
Kovacs, T., & Bull, L. (2007). Toward a better understanding of rule initialisation and deletion. In H. Lipson (Ed.), Proceedings of the 2007 GECCO Conference on Genetic and Evolutionary Computation. , (2777-2780). https://doi.org/10.1145/1274000.1274060

A number of heuristics have been used in Learning Classifier Systems to initialise parameters of new rules, to adjust fitness of parent rules when they generate offspring, and to select rules for deletion. Some have not been studied in the literature... Read More about Toward a better understanding of rule initialisation and deletion.

Fuzzy-XCS: A Michigan genetic fuzzy system (2007)
Journal Article
Casillas, J., Carse, B., & Bull, L. (2007). Fuzzy-XCS: A Michigan genetic fuzzy system. IEEE Transactions on Fuzzy Systems, 15(4), 536-550. https://doi.org/10.1109/TFUZZ.2007.900904

The issue of finding fuzzy models with an interpretability as good as possible without decreasing the accuracy is one of the main research topics on genetic fuzzy systems. When they are used to perform online reinforcement learning by means of Michig... Read More about Fuzzy-XCS: A Michigan genetic fuzzy system.

Learning classifier system ensembles with rule-sharing (2007)
Journal Article
Bull, L., Studley, M., Bagnall, A., & Whittley, I. (2007). Learning classifier system ensembles with rule-sharing. IEEE Transactions on Evolutionary Computation, 11(4), 496-502. https://doi.org/10.1109/TEVC.2006.885163

This paper presents an investigation into exploiting the population-based nature of learning classifier systems (LCSs) for their use within highly parallel systems. In particular, the use of simple payoff and accuracy-based LCSs within the ensemble m... Read More about Learning classifier system ensembles with rule-sharing.

Mining breast cancer data with XCS (2007)
Presentation / Conference
Kharbat, F., Bull, L., & Odeh, M. (2007, June). Mining breast cancer data with XCS. Paper presented at Proceedings of the 9th annual conference on Genetic and evolutionary computation

Towards clustering with XCS (2007)
Presentation / Conference
Tamee, K., Bull, L., & Pinngern, O. (2007, June). Towards clustering with XCS. Paper presented at Proceedings of the 9th annual conference on Genetic and evolutionary computation

Ycsc: a modified clustering technique based on lcs (2007)
Journal Article
Tamee, K., Bull, L., & Pinngern, O. (2007). Ycsc: a modified clustering technique based on lcs. Journal of Digital Information Management, 5(3), 160-166

This paper presents a novel approach to clustering using a simple accuracy-based Learning Classifier System with a modification to the original YCS fitness function has been found to improve the identification of less-separated data sets. Our approac... Read More about Ycsc: a modified clustering technique based on lcs.

Unconventional computing 2007 (2007)
Book
Adamatzky, A., de Lacy Costello, B., Bull, L., Stepney, S., & Teuscher, C. (2007). Unconventional computing 2007. Frome: Luniver Press

2007 index IEEE transactions on evolutionary computation vol. 11 (2007)
Journal Article
Aguilar-Ruiz, J., Alfonseca, M., Alonso, J., Alvarruiz, F., Arnold, D., Baesens, B., …Bull, L. (2007). 2007 index IEEE transactions on evolutionary computation vol. 11. IEEE Transactions on Evolutionary Computation, 11(6), 791-796. https://doi.org/10.1109/TEVC.2007.913016

This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also b... Read More about 2007 index IEEE transactions on evolutionary computation vol. 11.

Backpropagation in accuracy-based neural learning classifier systems (2007)
Book Chapter
O'Hara, T., & Bull, L. (2007). Backpropagation in accuracy-based neural learning classifier systems. In J. Bacardit, E. Bernadó-Mansilla, M. V. Butz, T. Kovacs, X. Llorà, & K. Takadama (Eds.), Learning Classifier Systems (25-39). Springer Verlag. https://doi.org/10.1007/978-3-540-71231-2_3

Learning Classifier Systems traditionally use a binary string rule representation with wildcards added to allow for generalizations over the problem encoding. We have presented a neural network-based representation to aid their use in complex problem... Read More about Backpropagation in accuracy-based neural learning classifier systems.

Using XCS to describe continuous-valued problem spaces (2007)
Conference Proceeding
Wyatt, D., Bull, L., & Parmee, I. (2007). Using XCS to describe continuous-valued problem spaces. https://doi.org/10.1007/978-3-540-71231-2_21

Learning classifier systems have previously been shown to have some application in single-step tasks. This paper extends work in the area by applying the classifier system to progressively more complex multi-modal test environments, each with typical... Read More about Using XCS to describe continuous-valued problem spaces.

A learning classifier system approach to clustering (2006)
Presentation / Conference
Tamee, K., Bull, L., & Pinngern, O. (2006, October). A learning classifier system approach to clustering. Paper presented at Intelligent Systems Design and Applications, 2006. ISDA'06. Sixth International Conference on, Jinan, China

Electrophysiological measurements in three-dimensional in vivo-mimetic organotypic cell cultures: Preliminary studies with hen embryo brain spheroids (2006)
Journal Article
Uroukov, I. S., Ma, M., Bull, L., & Purcell, W. M. (2006). Electrophysiological measurements in three-dimensional in vivo-mimetic organotypic cell cultures: Preliminary studies with hen embryo brain spheroids. Neuroscience Letters, 404(1-2), 33-38. https://doi.org/10.1016/j.neulet.2006.05.016

Using three-dimensional artificial tissue constructs shown to offer organotypic functionality, hen embryo brain spheroids were used as a novel electrophysiological paradigm. For the first time, single spontaneous action potentials were recorded from... Read More about Electrophysiological measurements in three-dimensional in vivo-mimetic organotypic cell cultures: Preliminary studies with hen embryo brain spheroids.

Variance stabilizing regression ensembles for environmental models (2006)
Presentation / Conference
Bagnall, A., Whittley, I., Studley, M., Pettipher, M., Tekiner, F., & Bull, L. (2006, July). Variance stabilizing regression ensembles for environmental models. Paper presented at Neural Networks, 2006. IJCNN'06. International Joint Conference on, Vancouver, Canada

Towards machine learning control of chemical computers (2006)
Book Chapter
Budd, A., Stone, C., Masere, J., Adamatzky, A., de Lacy Costello, B., & Bull, L. (2006). Towards machine learning control of chemical computers. In A. Adamatzky, & C. Teuscher (Eds.), From Utopian to Genuine Unconventional Computers (17-36). Frome, UK: Luniver Press

A comparison of DWT/PAA and DFT for time series classification (2006)
Presentation / Conference
Bagnall, A. J., Whittley, I. M., Janacek, G. J., Kemsley, K., Studley, M., & Bull, L. (2006, June). A comparison of DWT/PAA and DFT for time series classification. Paper presented at International conference on Data Mining (DMIN '06), Las Vegas, US

Discrete Fourier transforms (DFT) and Haar two, PAA is identical to a Haar Wavelet transformation [61. wavelets (DWT) were proposed for the use in time series data mining over five years ago and have since proved to be popular algorithms for the tran... Read More about A comparison of DWT/PAA and DFT for time series classification.

Using a learning classifier system for clustering (2006)
Presentation / Conference
Tamee, K., Bull, L., Pinngern, O., Rojanavasu, P., & Srinil, P. (2006, June). Using a learning classifier system for clustering. Paper presented at International Symposium on Communications and Information Technologies, 2006. ISCIT'06

A neural learning classifier system with self-adaptive constructivism for mobile robot control (2006)
Journal Article
Hurst, J., & Bull, L. (2006). A neural learning classifier system with self-adaptive constructivism for mobile robot control. Artificial Life, 12(3), 353-380. https://doi.org/10.1162/artl.2006.12.3.353

For artificial entities to achieve true autonomy and display complex lifelike behavior, they will need to exploit appropriate adaptable learning algorithms. In this context adaptability implies flexibility guided by the environment at any given time... Read More about A neural learning classifier system with self-adaptive constructivism for mobile robot control.

SCDM User Guide (2006)
Other
Studley, M., Whittley, I. M., Tekiner, F., Bull, L., Bagnall, A. J., & Pettipher, M. (2006). SCDM User Guide

Coevolutionary species adaptation genetic algorithms: A continuing SAGA on coupled fitness landscapes (2005)
Journal Article
Bull, L. (2005). Coevolutionary species adaptation genetic algorithms: A continuing SAGA on coupled fitness landscapes. Lecture Notes in Artificial Intelligence, 3630 LNAI, 322-331. https://doi.org/10.1007/11553090_33

The Species Adaptation Genetic Algorithm (SAGA) was introduced to facilitate the open-ended evolution of artificial systems. The approach enables genotypes to increase in length through appropriate mutation operators and has been successfully exploit... Read More about Coevolutionary species adaptation genetic algorithms: A continuing SAGA on coupled fitness landscapes.

X-TCS: Accuracy-based learning classifier system robotics (2005)
Journal Article
Studley, M., & Bull, L. (2005). X-TCS: Accuracy-based learning classifier system robotics. https://doi.org/10.1109/CEC.2005.1554954

Although most learning classifier system (LCS) research uses the accuracy-based XCS, it had never been used to control a physical robot before. In comparison to purely evolutionary or purely reinforcement learning approaches, an LCS should be faster... Read More about X-TCS: Accuracy-based learning classifier system robotics.

Towards predicting spatial complexity: a learning classifier system approach to the identification of cellular automata (2005)
Presentation / Conference
Bull, L., Lawson, I., Adamatzky, A., & de Lacy Costello, B. (2005, September). Towards predicting spatial complexity: a learning classifier system approach to the identification of cellular automata. Paper presented at IEEE Congress on Evolutionary Computation, 2005, Edinburgh, UK

This paper presents a novel approach to the programming of automata-based simulation and computation using a machine learning technique. The identification of lattice-based automata for real-world applications is cast as a data mining problem. Our ap... Read More about Towards predicting spatial complexity: a learning classifier system approach to the identification of cellular automata.

Coevolutionary species adaptation genetic algorithms: growth and mutation on coupled fitness landscapes (2005)
Presentation / Conference
Bull, L. (2005, September). Coevolutionary species adaptation genetic algorithms: growth and mutation on coupled fitness landscapes. Paper presented at 2005 IEEE Congress on Eolutionary Computation, Edinburgh, UK

The species adaptation genetic algorithm (SAGA) was introduced to facilitate the open-ended evolution of artificial systems. The approach enables genotypes to increase in length through appropriate mutation operators. Most recently, this has been und... Read More about Coevolutionary species adaptation genetic algorithms: growth and mutation on coupled fitness landscapes.

Genetic programming with a genetic algorithm for feature construction and selection (2005)
Journal Article
Smith, M. G., & Bull, L. (2005). Genetic programming with a genetic algorithm for feature construction and selection. Genetic Programming and Evolvable Machines, 6(3), 265-281. https://doi.org/10.1007/s10710-005-2988-7

The use of machine learning techniques to automatically analyse data for information is becoming increasingly widespread. In this paper we primarily examine the use of Genetic Programming and a Genetic Algorithm to pre-process data before it is class... Read More about Genetic programming with a genetic algorithm for feature construction and selection.

An accuracy-based fuzzy classifier system (2004)
Presentation / Conference
Casillias, J., Carse, B., & Bull, L. (2004, June). An accuracy-based fuzzy classifier system. Paper presented at 12th Spanish Conference on Fuzzy Logic and Technologies

Using genetic programming for feature creation with a genetic algorithm feature selector (2004)
Journal Article
Smith, M. G., & Bull, L. (2004). Using genetic programming for feature creation with a genetic algorithm feature selector. Lecture Notes in Artificial Intelligence, 3242, 1163-1171. https://doi.org/10.1007/978-3-540-30217-9_117

The use of machine learning techniques to automatically analyse data for information is becoming increasingly widespread. In this paper we primarily examine the use of Genetic Programming and a Genetic Algorithm to preprocess data before it is classi... Read More about Using genetic programming for feature creation with a genetic algorithm feature selector.

Feature construction and selection using genetic programming and a genetic algorithm (2003)
Journal Article
Smith, M. G., & Bull, L. (2003). Feature construction and selection using genetic programming and a genetic algorithm. Lecture Notes in Artificial Intelligence, 2610, 229-237. https://doi.org/10.1007/3-540-36599-0_21

The use of machine learning techniques to automatically analyse data for information is becoming increasingly widespread. In this paper we examine the use of Genetic Programming and a Genetic Algorithm to pre-process data before it is classified usin... Read More about Feature construction and selection using genetic programming and a genetic algorithm.

Comparing learning classifier systems for continuous-valued online environments (2003)
Journal Article
Stone, C., & Bull, L. (2003). Comparing learning classifier systems for continuous-valued online environments

We investigate Learning Classifier Systems for online environments that consist of real-valued states and which require every action made by the agent to count towards its performance. Two Learning Classifier System architectures are considered, ZCS... Read More about Comparing learning classifier systems for continuous-valued online environments.

For Real! XCS with Continuous-Valued Inputs (2003)
Journal Article
Stone, C., & Bull, L. (2003). For Real! XCS with Continuous-Valued Inputs. Evolutionary Computation, 11(3), 299-336. https://doi.org/10.1162/106365603322365315

Many real-world problems are not conveniently expressed using the ternary representation typically used by Learning Classifier Systems and for such problems an interval-based representation is preferable. We analyse two interval-based representations... Read More about For Real! XCS with Continuous-Valued Inputs.

Addressing policy objectives of traffic control using evolutionary algorithms (2002)
Presentation / Conference
Sha'Aban, J., Tomlinson, A., HEYDECKER, B., & Bull, L. (2002, September). Addressing policy objectives of traffic control using evolutionary algorithms. Paper presented at European Transport Conference 2002, Cambridge, UK

This paper presents preliminary results from an ongoing research project that is investigating traffic management and signal control of evolutionary algorithms that use machine learning. It describes the application of novel technologies of machine l... Read More about Addressing policy objectives of traffic control using evolutionary algorithms.

Towards the use of XCS in interactive evolutionary design (2002)
Book Chapter
Bull, L., Wyatt, D., & Parmee, I. (2002). Towards the use of XCS in interactive evolutionary design. In W. Langdon (Ed.), GECCO-2002: proceedings of the Genetic and Evolutionary Computation Conference (951). Morgan Kaufmann Publishers

Adaptive traffic control using evolutionary algorithms (2002)
Presentation / Conference
Sha'Aban, J., Tomlinson, A., Heydecker, B. G., & Bull, L. (2002, June). Adaptive traffic control using evolutionary algorithms. Paper presented at 13th Mini-Euro Conference, Bari, Italy

Lookahead and latent learning in ZCS (2002)
Presentation / Conference
Bull, L. (2002, June). Lookahead and latent learning in ZCS. Paper presented at Proceedings of the Genetic and Evolutionary Computation Conference 2002

ZCS redux (2002)
Journal Article
Bull, L., & Hurst, J. (2002). ZCS redux. Evolutionary Computation, 10(2), 185-205. https://doi.org/10.1162/106365602320169848

Learning classifier systems traditionally use genetic algorithms to facilitate rule discovery, where rule fitness is payoff based. Current research has shifted to the use of accuracy-based fitness. This paper re-examines the use of a particular payof... Read More about ZCS redux.

On using constructivism in neural classifier systems (2002)
Conference Proceeding
Bull, L. (2002). On using constructivism in neural classifier systems. In J. J. Merelo, P. Adamidis, & H. Beyer (Eds.), In Parallel Problem Solving from Nature — PPSN VII. , (558-567). https://doi.org/10.1007/3-540-45712-7_54

For artificial entities to achieve true autonomy and display complex life-like behaviour they will need to exploit appropriate adaptable learning algorithms. In this sense adaptability implies flexibility guided by the environment at any given time a... Read More about On using constructivism in neural classifier systems.

Consideration of multiple objectives in neural learning classifier systems (2002)
Conference Proceeding
Bull, L., & Studley, M. (2002). Consideration of multiple objectives in neural learning classifier systems. In J. J. Merelo, P. Adamidis, & H. Beyer (Eds.), Parallel Problem Solving from Nature—PPSN VII. , (549-557). https://doi.org/10.1007/3-540-45712-7_53

© Springer-Verlag Berlin Heidelberg 2002. For effective use in a number of problem domains Learning Classifier Systems must be able to manage multiple objectives. This paper explicitly considers the case of developing the controller for a simulated m... Read More about Consideration of multiple objectives in neural learning classifier systems.

Initial modifications to XCS for use in interactive evolutionary design (2002)
Conference Proceeding
Bull, L., Wyatt, D., & Parmee, I. (2002). Initial modifications to XCS for use in interactive evolutionary design. In J. J. Merelo, P. Adamidis, & H. Beyer (Eds.), Parallel Problem Solving from Nature—PPSN VII. , (568-577). https://doi.org/10.1007/3-540-45712-7_55

© Springer-Verlag Berlin Heidelberg 2002. Learning classifier systems represent a technique by which various characteristics of a given problem space may be deduced and presented to the user in a readable format. In this paper we present results from... Read More about Initial modifications to XCS for use in interactive evolutionary design.

I theory-a self-adaptive XCS (2002)
Journal Article
Hurst, J., & Bull, L. (2002). I theory-a self-adaptive XCS. Lecture Notes in Artificial Intelligence, 2321, 57-73

A self-adaptive XCS (2002)
Conference Proceeding
Hurst, J., & Bull, L. (2002). A self-adaptive XCS. In P. L. Lanzi, W. Stolzmann, & S. W. Wilson (Eds.), In Advances in Learning Classifier Systems. , (57-73). https://doi.org/10.1007/3-540-48104-4_5

Self-adaptation has been used extensively to control parameters in various forms of evolutionary computation. The concept was first introduced with evolutionary strategies and it is now often used to control genetic algorithms. This paper describes t... Read More about A self-adaptive XCS.

TCS learning classifier system controller on a real robot (2002)
Journal Article
Hurst, J., Bull, L., & Melhuish, C. (2002). TCS learning classifier system controller on a real robot. Lecture Notes in Artificial Intelligence, 2439, 588-597. https://doi.org/10.1007/3-540-45712-7_57

To date there have been few implementation of Holland’s Learning Classifier System (LCS) on real robots. The paper introduces a Temporal Classifier System (TCS), an LCS derived from Wilson’s ZCS. Traditional LCS have the ability to generalise over th... Read More about TCS learning classifier system controller on a real robot.

ZCS and TCS learning classifier system controllers on real robots (2002)
Journal Article
Hurst, J., Bull, L., & Melhuish, C. (2002). ZCS and TCS learning classifier system controllers on real robots

To date there has only been one implementation of Holland's Learning Classifier System (LCS) on real robots. In this paper the use of Wilson's ZCS system is described for an obstacle avoidance task. Although the task is simple it does present some ad... Read More about ZCS and TCS learning classifier system controllers on real robots.

GECCO 2002: Proceedings of the genetic and evolutionary computation conference (2002)
Book Chapter
Langdon, W., Cant{\'u}-Paz, E., Mathias, K., Roy, R., Davis, D., Poli, R., …Bull, L. (2002). GECCO 2002: Proceedings of the genetic and evolutionary computation conference. In W. Langdon, E. Cant u Paz, K. Mathias, R. Roy, D. Davis, R. Poli, …L. Bull (Eds.), GECCO-2002: proceedings of the genetic and evolutionary computation conference. Morgan Kaufmann Publishers

Simple models of coevolutionary genetic algorithms (2001)
Journal Article
Bull, L. (2001). Simple models of coevolutionary genetic algorithms. Artificial Life and Robotics, 5(1), 58-66. https://doi.org/10.1007/BF02481321

The use of evolutionary computing techniques in coevolutionary/multiagent systems is becoming increasingly popular. This paper presents some simple models of the genetic algorithm in such systems, with the aim of examining the effects of different ty... Read More about Simple models of coevolutionary genetic algorithms.

Coevolving functions in genetic programming (2001)
Journal Article
Ahluwalia, M., & Bull, L. (2001). Coevolving functions in genetic programming. Journal of Systems Architecture, 47(7), 573-585. https://doi.org/10.1016/S1383-7621%2801%2900016-9

In this paper we introduce a new approach to the use of automatically defined functions (ADFs) within genetic programming. The technique consists of evolving a number of separate sub-populations of functions which can be used by a population of evolv... Read More about Coevolving functions in genetic programming.

Simple Markov models of the genetic algorithm in classifier systems: multi-step tasks (2001)
Journal Article
Bull, L. (2001). Simple Markov models of the genetic algorithm in classifier systems: multi-step tasks. Lecture Notes in Artificial Intelligence, 1996, 29-36

Abstract Michigan-style Classifier Systems use Genetic Algorithms to facilitate rule discovery. This paper presents a simple Markov model of the algorithm in such systems, with the aim of examining the effects of different types of interdependence be... Read More about Simple Markov models of the genetic algorithm in classifier systems: multi-step tasks.

A self-adaptive classifier system (2001)
Conference Proceeding
Hurst, J., & Bull, L. (2001). A self-adaptive classifier system. In P. L. Lanzi, W. Stolzmann, & S. W. Wilson (Eds.), Advances in Learning Classifier Systems. , (70-79). https://doi.org/10.1007/3-540-44640-0_6

© Springer-Verlag Berlin Heidelberg 2001. The use and benefits of self-adaptive parameters, particularly mutation, are well-known within evolutionary computing. In this paper we examine the use of parameter self-adaptation in Michigan-style Classifie... Read More about A self-adaptive classifier system.

A communication architecture for multi-agent learning systems (2000)
Book Chapter
Ireson, N., Cao, Y., Bull, L., & Miles, R. (2000). A communication architecture for multi-agent learning systems. In S. Cagnoni, R. Poli, G. D. Smith, D. Corne, M. Oates, E. Hart, …T. C. Fogarty (Eds.), Real-World Applications of Evolutionary Computing: EvoWorkshops 2000 (119-147). Springer

Self-adaptive mutation in ZCS controllers (2000)
Journal Article
Bull, L., & Hurst, J. (2000). Self-adaptive mutation in ZCS controllers. Lecture Notes in Artificial Intelligence, 1803, 339-346. https://doi.org/10.1007/3-540-45561-2_33

© Springer-Verlag Berlin Heidelberg 2000. The use and benefits of self-adaptive mutation operators are well-known within evolutionary computing. In this paper we examine the use of self-adaptive mutation in Michigan-style Classifier Systems with the... Read More about Self-adaptive mutation in ZCS controllers.

Self-adaptive mutation in classifier system controllers (2000)
Book Chapter
Bull, L., Hurst, J., & Tomlinson, A. (2000). Self-adaptive mutation in classifier system controllers. In J. Meyer, A. Berthoz, D. Floreano, H. L. Roitblat, & S. W. Wilson (Eds.), From Animals to Animats 6 (460-467). MIT Press

Distributed learning control of traffic signals (2000)
Journal Article
Bull, L., Cao, Y. J., Ireson, N., Bull, L., & Miles, R. (2000). Distributed learning control of traffic signals. Lecture Notes in Artificial Intelligence, 1803, 117-126. https://doi.org/10.1007/3-540-45561-2_12

© Springer-Verlag Berlin Heidelberg 2000. This paper presents a distributed learning control strategy for traffic signals. The strategy uses a fully distributed architecture in which there is effectively only one (low) level of control. Such strategy... Read More about Distributed learning control of traffic signals.

A zeroth level corporate classifier system (1999)
Presentation / Conference
Tomlinson, A., & Bull, L. (1999, June). A zeroth level corporate classifier system. Paper presented at Genetic and Evolutionary Computation Conference (GECCO’99)

A genetic programming-based classifier system (1999)
Presentation / Conference
Ahluwalia, M., Bull, L., & Banzhaf, W. (1999, June). A genetic programming-based classifier system. Paper presented at Genetic and Evolutionary Computation Conference (GECCO-99)

On the evolution of multicellularity and eusociality (1999)
Journal Article
Bull, L. (1999). On the evolution of multicellularity and eusociality. Artificial Life, 5(1), 1-15. https://doi.org/10.1162/106454699568656

In this article versions of the abstract NKC model are used to examine the conditions under which two significant evolutionary phenomena - multicellularity and eusociality - are likely to occur and why. First, comparisons in evolutionary performance... Read More about On the evolution of multicellularity and eusociality.

Design of a traffic junction controller using classifier system and fuzzy logic (1999)
Journal Article
Cao, Y. J., Ireson, N., Bull, L., & Miles, R. (1999). Design of a traffic junction controller using classifier system and fuzzy logic. Lecture Notes in Artificial Intelligence, 1625, 342-353. https://doi.org/10.1007/3-540-48774-3_40

© Springer-Verlag Berlin Heidelberg 1999. Traffic control in laige cities is a difficult and non-trivial optimization problem. Most of the automated urban traffic control systems aie based on deterministic algorithms and have a multi-level architectu... Read More about Design of a traffic junction controller using classifier system and fuzzy logic.

Co-evolving functions in genetic programming: Dynamic ADF creation using GLiB (1998)
Book Chapter
Ahluwalia, M., & Bull, L. (1998). Co-evolving functions in genetic programming: Dynamic ADF creation using GLiB. In W. V. Porto, N. Saravanan, D. E. Waagen, & A. Eiben (Eds.), Proceedings of the 7th International Conference on Evolutionary Programming VII (809-818). London: Springer-Verlag

Evolutionary computing in multi-agent environments: Operators (1998)
Conference Proceeding
Bull, L. (1998). Evolutionary computing in multi-agent environments: Operators. In V. W. Porto, N. Saravanan, D. Waagen, & A. E. Eiben (Eds.), In EP 1998: Evolutionary Programming VII. , (43-52). https://doi.org/10.1007/BFb0040758

This paper examines a key aspect of applying evolutionary computing techniques to multi-agent systems: a comparison in the performance of the genetic operators of mutation and recombination. Using the tuneable NKC model of multi-agent evolution it is... Read More about Evolutionary computing in multi-agent environments: Operators.

On ZCS in multi-agent environments (1998)
Conference Proceeding
Bull, L. (1998). On ZCS in multi-agent environments. In A. Eiben, T. Bäck, M. Schoenauer, & H. Schwefel (Eds.), Parallel Problem Solving from Nature—PPSN V. , (471-480). https://doi.org/10.1007/BFb0056889

This paper examines the performance of the ZCS Michigan-style classifier system in multi-agent environments. Using an abstract multi-agent model the effects of varying aspects of the performance, reinforcement and discovery components are examined. I... Read More about On ZCS in multi-agent environments.

A corporate classifier system (1998)
Conference Proceeding
Tomlinson, A., & Bull, L. (1998). A corporate classifier system. In A. E. Eiben, T. Bäck, M. Schoenauer, & H. Schwefel (Eds.), Parallel Problem Solving from Nature—PPSN V. , (550-559). https://doi.org/10.1007/BFb0056897

Based on the proposals of Wilson and Goldberg we introduce a macro-level evolutionary operator which creates structural links between rules in the ZCS model and thus forms "corporations" of rules within the classifier system population. Rule co-depen... Read More about A corporate classifier system.

On the evolution of Eukaryotes (1997)
Presentation / Conference
Bull, L. (1997, October). On the evolution of Eukaryotes. Paper presented at Mathematical and computational biology: Computational morphogenesis, hierarchical complexity, and digital evolution: an international workshop, University of Aizu, Aizu-Wakamatsu City, Japan

Horizontal gene transfer in endosymbiosis (1997)
Book Chapter
Bull, L., & Fogarty, T. (1997). Horizontal gene transfer in endosymbiosis. In L. Bull (Ed.), Proceedings of the 5th International workshop on Artificial Life: Synthesis and simulation of living systems (77-84). Bradford book

On the evolution of multicellularity (1997)
Book Chapter
Bull, L. (1997). On the evolution of multicellularity. In P. Husbands, & I. Harvey (Eds.), Fourth European Conference on Artificial Life [ECAL '97] (190-196). London: Cambridge

Evolutionary computing in multi-agent environments: Speciation and symbiogenesis (1996)
Journal Article
Bull, L., Bull, L., & Fogarty, T. C. (1996). Evolutionary computing in multi-agent environments: Speciation and symbiogenesis. Lecture Notes in Artificial Intelligence, 1141, 12-21. https://doi.org/10.1007/3-540-61723-X_965

© 1996, Springer-Verlag. All rights reserved. In this paper we introduce two macro-level operators to enhance the use of population-based evolutionary computing techniques in multiagent environments: speciation and symbiogenesis. We describe their us... Read More about Evolutionary computing in multi-agent environments: Speciation and symbiogenesis.

Optimising individual control rules and multiple communicating rule-based control systems with parallel distributed genetic algorithms (1995)
Journal Article
Fogarty, T. C., & Bull, L. (1995). Optimising individual control rules and multiple communicating rule-based control systems with parallel distributed genetic algorithms. IEE Proceedings Control Theory and Applications, 142(3), 211-215. https://doi.org/10.1049/ip-cta%3A19951864

Genetic algorithms can be used to optimise either individual process-control rules or complete rule-based controllers. The paper describes the optimisation of individual rules to control combustion in multiple burner installations. To solve more comp... Read More about Optimising individual control rules and multiple communicating rule-based control systems with parallel distributed genetic algorithms.

Artificial endosymbiosis (1995)
Journal Article
Pipe, A. G., Bull, L., Bull, L., Fogarty, T. C., & Pipe, A. G. (1995). Artificial endosymbiosis. Lecture Notes in Artificial Intelligence, 929, 273-289. https://doi.org/10.1007/3-540-59496-5_305

© Springer-Verlag Berlin Heidelberg 1995. Symbiosis is the phenomenon in which organisms of different species live together in close association, resulting in a raised level of fitness for one or more of the organisms. Endosymbiosis is the name given... Read More about Artificial endosymbiosis.

Parallel evolution of communicating classifier systems (1994)
Presentation / Conference
Bull, L., & Fogarty, T. C. (1994, June). Parallel evolution of communicating classifier systems. Paper presented at Proceedings of the First IEEE Conference on Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence

An evolution strategy and genetic algorithm hybrid: An initial implementation and first results (1994)
Conference Proceeding
Bull, L., & Fogarty, T. C. (1994). An evolution strategy and genetic algorithm hybrid: An initial implementation and first results. In T. C. Fogarty (Ed.), In AISB EC 1994: Evolutionary Computing. , (95-102). https://doi.org/10.1007/3-540-58483-8_8

Evolution Strategies (ESs)[15] and Genetic Algorithms (GAs)[13] have both been used to optimise functions, using the natural process of evolution as inspiration for their search mechanisms. The ES uses gene mutation as it’s main search operator whils... Read More about An evolution strategy and genetic algorithm hybrid: An initial implementation and first results.

Co-evolving communicating classifier systems for tracking (1993)
Presentation / Conference
Bull, L., & Fogarty, T. C. (1993, June). Co-evolving communicating classifier systems for tracking. Paper presented at Proceedings of the International Conference on Neural Networks and Genetic Algoriths

I Theory (1984)
Journal Article
Baum, E., Durdanovic, I., Bull, L., Butz, M., Goldberg, D., Stolzmann, W., …Kovacs, T. (1984). I Theory