Forrest Parallelism and Programming in Classifier Systems

1. Auflage 2014
ISBN: 978-0-08-051355-3
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 232 Seiten, Web PDF

Parallelism and Programming in Classifier Systems deals with the computational properties of the underlying parallel machine, including computational completeness, programming and representation techniques, and efficiency of algorithms. In particular, efficient classifier system implementations of symbolic data structures and reasoning procedures are presented and analyzed in detail. The book shows how classifier systems can be used to implement a set of useful operations for the classification of knowledge in semantic networks. A subset of the KL-ONE language was chosen to demonstrate these operations. Specifically, the system performs the following tasks: (1) given the KL-ONE description of a particular semantic network, the system produces a set of production rules (classifiers) that represent the network; and (2) given the description of a new term, the system determines the proper location of the new term in the existing network. These two parts of the system are described in detail. The implementation reveals certain computational properties of classifier systems, including completeness, operations that are particularly natural and efficient, and those that are quite awkward. The book shows how high-level symbolic structures can be built up from classifier systems, and it demonstrates that the parallelism of classifier systems can be exploited to implement them efficiently. This is significant since classifier systems must construct large sophisticated models and reason about them if they are to be truly ''intelligent.'' Parallel organizations are of interest to many areas of computer science, such as hardware specification, programming language design, configuration of networks of separate machines, and artificial intelligence This book concentrates on a particular type of parallel organization and a particular problem in the area of AI, but the principles that are elucidated are applicable in the wider setting of computer science.

Autoren/Hrsg.

Forrest, Stephanie

Inhaltsverzeichnis

1;Front Cover;1
2;Parallelism and Programming in Classifier Systems;4
3;Copyright Page;5
4;Table of Contents;6
5;Dedication;11
6;List of Figures;8
7;List of Appendices;9
8;Preface;10
9;Chapter 1. Introduction;12
9.1;1.1 Parallelism and Classifier Systems;13
9.2;1.2 Classification and KL-ONE;15
9.3;1.3 Subsymbolic Models of Intelligence;16
9.4;1.4 Overview;17
10;Chapter 2. Background Information;20
10.1;2.1 Parallelism;20
10.2;2.2 Classifier Systems;27
10.3;2.3 KL-ONE;35
10.4;2.4 Summary;44
11;Chapter 3. Approach;46
11.1;3.1 Implementation;46
11.2;3.2 Evaluation;49
11.3;3.3 Summary;50
12;Chapter 4. Classifier Systems;52
12.1;4.1 Computational Properties of Classifier Systems;52
12.2;4.2 Classifier System Algorithms;56
12.3;4.3 Summary;74
13;Chapter 5. Classifier System Implementation of KL-ONE;76
13.1;5.1 Representation;76
13.2;5.2 Algorithms;87
13.3;5.3 Summary;114
14;Chapter 6 Analysis of Results;116
14.1;6.1 Time of Computation;117
14.2;6.2 Number and Size of Processors;120
14.3;6.3 Inter-Processor Communication;121
14.4;6.4 Comparison with Sequential Algorithm;122
14.5;6.5 Computational Tradeoffs;126
14.6;6.6 Summary of Results;126
15;Chapter 7. Conclusions;130
15.1;7.1 Classifer Systems;130
15.2;7.2 KL-ONE;133
15.3;7.3 Parallelism;134
16;APPENDICES: Backus Normal Form Description of Input Language;138
17;Bibliography;218