Advertisement

Anticipatory Learning Classifier Systems

  • Martin V. Butz

Part of the Genetic Algorithms and Evolutionary Computation book series (GENA, volume 4)

Table of contents

  1. Front Matter
    Pages i-xxviii
  2. Martin V. Butz
    Pages 1-22
  3. Martin V. Butz
    Pages 23-49
  4. Martin V. Butz
    Pages 51-80
  5. Martin V. Butz
    Pages 81-97
  6. Martin V. Butz
    Pages 99-114
  7. Martin V. Butz
    Pages 115-120
  8. Martin V. Butz
    Pages 121-138
  9. Back Matter
    Pages 139-172

About this book

Introduction

Anticipatory Learning Classifier Systems describes the state of the art of anticipatory learning classifier systems-adaptive rule learning systems that autonomously build anticipatory environmental models. An anticipatory model specifies all possible action-effects in an environment with respect to given situations. It can be used to simulate anticipatory adaptive behavior.

Anticipatory Learning Classifier Systems highlights how anticipations influence cognitive systems and illustrates the use of anticipations for (1) faster reactivity, (2) adaptive behavior beyond reinforcement learning, (3) attentional mechanisms, (4) simulation of other agents and (5) the implementation of a motivational module. The book focuses on a particular evolutionary model learning mechanism, a combination of a directed specializing mechanism and a genetic generalizing mechanism. Experiments show that anticipatory adaptive behavior can be simulated by exploiting the evolving anticipatory model for even faster model learning, planning applications, and adaptive behavior beyond reinforcement learning.

Anticipatory Learning Classifier Systems gives a detailed algorithmic description as well as a program documentation of a C++ implementation of the system.

Keywords

agents algorithms behavior cognitive science cognitive systems evolution learning machine learning optimization reinforcement learning simulation

Authors and affiliations

  • Martin V. Butz
    • 1
  1. 1.University of WürzburgGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-0891-5
  • Copyright Information Kluwer Academic Publishers 2002
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-5290-7
  • Online ISBN 978-1-4615-0891-5
  • Series Print ISSN 1568-2587
  • Buy this book on publisher's site