All Outputs (127)

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.

Adaptive gait acquisition using multi-agent learning for wall climbing robots (1995)
Journal Article
Bull, L., Fogarty, T. C., Mikami, S., & Thomas, J. (1995). Adaptive gait acquisition using multi-agent learning for wall climbing robots

Evolving multi-agent systems (1995)
Journal Article
Fogarty, T. C., Bull, L., & Carse, B. (1995). Evolving multi-agent systems

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

Discrete and fuzzy dynamical genetic programming in the XCSF learning classifier system
Journal Article
Preen, R. J., & Bull, L. Discrete and fuzzy dynamical genetic programming in the XCSF learning classifier system. https://doi.org/10.1007/s00500-013-1044-4

A spiking neural learning classifier system
Journal Article
Howard, G. D., Bull, L., & Lanzi, P. L. A spiking neural learning classifier system

Learning Classifier Systems (LCS) are population-based reinforcement learners used in a wide variety of applications. This paper presents a LCS where each traditional rule is represented by a spiking neural network, a type of network with dynamic int... Read More about A spiking neural learning classifier system.

On the application of hierarchical coevolutionary genetic algorithms: Recombination and evaluation partners
Journal Article
Aickelin, U., & Bull, L. On the application of hierarchical coevolutionary genetic algorithms: Recombination and evaluation partners