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All Outputs (18)

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

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

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.

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.

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.

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

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.

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.

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.

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.