Anticipatory Learning Classifier Systems / Edition 1by Martin V. Butz
Pub. Date: 01/01/2002
Publisher: Springer US
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… See more details below
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.
- Springer US
- Publication date:
- Genetic Algorithms and Evolutionary Computation Series, #4
- Edition description:
- Product dimensions:
- 0.56(w) x 9.21(h) x 6.14(d)
Table of Contents
List of Figures. List of Tables. Foreword. Preface. Acknowledgments.
3. Experiments with ACS2.
5. Model Exploitation.
6. Related Systems.
7. Summary, Conclusions, and Future Work.
Appendices. Appendix A: Parameters in ACS2. Appendix B: Algorithmic Description of ACS2. Appendix C: ACS2 C++ Documentation. Appendix D: Glossary.
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Nice review of preceding work to get the reader up to speed. Occasional typos, mispelling and poor english detract from a volume that documents near state of the art research. Easy to obtain papers 'the references' in pdf format should complement the reading. No discussion is made of how evolving anticipatory classifiers parallel evolving state machines. The anticipatory classifier appears to loosely correspond to the next state pointer 'of an evolved state machine.' The source code for ACS on the Illigal site is prepared for a Linux system only. Being able to run various scenarios as one mentally digests a book is helpful as authors can easily forget readers don't have all the background required, just the desire to learn about a particular technique for their own reasons.