All Outputs (14)

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.

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.

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.

Imitation programming (2010)
Journal Article
Bull, L. (2010). Imitation programming. Lecture Notes in Artificial Intelligence, 6274 LNCS, 360-371. https://doi.org/10.1007/978-3-642-15323-5_31

Many nature-inspired mechanisms have been presented for computational design and optimization. This paper introduces a population-based approach inspired by a form of cultural learning - imitation. Imitation is typically defined as learning through t... Read More about Imitation programming.

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.

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.

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.

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.

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.

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.

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.

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.

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.