Anticipatory Learning Classifier Systems
Author | : Martin V. Butz |
Publisher | : Springer Science & Business Media |
Total Pages | : 418 |
Release | : 2002-01-31 |
ISBN-10 | : 0792376307 |
ISBN-13 | : 9780792376309 |
Rating | : 4/5 (309 Downloads) |
Download or read book Anticipatory Learning Classifier Systems written by Martin V. Butz and published by Springer Science & Business Media. This book was released on 2002-01-31 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.