Anticipatory Learning Classifier Systems (Genetic Algorithms and Evolutionary Computation)

    Anticipatory Learning Classifier Systems (Genetic Algorithms and Evolutionary Computation)
Authors Martin V. Butz
Year 2012
Publication Springer; 2002 edition (December 6, 2012)
ISBN 9780792376309
Pages 172 pages
Size 2967 KB
Format EPUB
Price 12 $ 2.4 $ Ben discount

Abstract

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.