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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.

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.

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.

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.