All Outputs (261)

A self-adaptive XCS (2002)
Presentation / Conference Contribution

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.

TCS learning classifier system controller on a real robot (2002)
Presentation / Conference Contribution

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.

ZCS and TCS learning classifier system controllers on real robots (2002)
Report

ZCS and TCS learning classifier system controllers on real robots (2002)
Journal Article

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.

GECCO 2002: Proceedings of the genetic and evolutionary computation conference (2002)
Book Chapter

An accuracy based corporate classifier system (2002)
Journal Article

Simple models of coevolutionary genetic algorithms (2001)
Journal Article

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

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.

On coevolutionary genetic algorithms (2001)
Journal Article

Simple Markov models of the genetic algorithm in classifier systems: multi-step tasks (2001)
Journal Article

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.

Simple markov models of the genetic algorithm in classifier systems: Multi-step tasks (2001)
Book Chapter

ZCS: Theory and practice: UWE Learning Classifier Systems Group Technical Report 01 (2001)
Report

An accuracy-based neural classifier system (2001)
Report

Learning Classifier Systems have traditionally used a binary representation, with wildcards added to facilitate generalization. As they are applied to more complex domains the simple representation can become limiting. In this paper we present result... Read More about An accuracy-based neural classifier system.

Self-adaptation in classifier system controllers (2001)
Journal Article

A self-adaptive classifier system (2001)
Presentation / Conference Contribution

© Springer-Verlag Berlin Heidelberg 2001. The use and benefits of self-adaptive parameters, particularly mutation, are well-known within evolutionary computing. In this paper we examine the use of parameter self-adaptation in Michigan-style Classifie... Read More about A self-adaptive classifier system.

An investigation into LCS road traffic junction controllers (2001)
Journal Article

A communication architecture for multi-agent learning systems (2000)
Book Chapter

On meme-gene coevolution (2000)
Journal Article

Self-adaptive mutation in ZCS controllers (2000)
Presentation / Conference Contribution

© 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.

Self-adaptive mutation in classifier system controllers (2000)
Book Chapter