Anticipatory Learning Classifier Systems

Anticipatory Learning Classifier Systems

by Martin V. Butz
     
 

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

Overview

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.

Editorial Reviews

Butz (U. of Würzburg, Germany) discusses the simulation and utilization of anticipations to a simulated learning environment in an artificial behavioral learning system. A major focus is on how an environmental model can be represented and learned in an artificial learning system, while a secondary, but significant, concern is an investigation of how the evolving artificial environmental model may influence the behavior of the artificial system. One particular anticipatory learning classifier system, ACS2, is introduced, along with the C++ code documentation and algorithmic descriptions. ACS2 forms condition-action-effect rules perceiving an environment and acting in that environment. The formed rules specify what may change after the execution of an action in a given situation. The primary goal of the system is to evolve a complete, accurate, and compact set of rules that fully represent an environmental model. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Product Details

ISBN-13:
9781461352907
Publisher:
Springer US
Publication date:
04/30/2013
Series:
Genetic Algorithms and Evolutionary Computation Series , #4
Edition description:
Softcover reprint of the original 1st ed. 2002
Pages:
172
Product dimensions:
6.14(w) x 9.21(h) x 0.43(d)

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