All Outputs (6)

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.