Parallel Processing for Artificial Intelligence (Machine Intelligence & Pattern Recognition) (v. 3)
โ Scribed by C.B. Suttner
- Publisher
- Elsevier Science & Technology
- Year
- 1997
- Tongue
- English
- Leaves
- 336
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
This is the third volume in an informal series of books about parallel processing for artificial intelligence. It is based on the assumption that the computational demands of many AI tasks can be better served by parallel architectures than by the currently popular workstations. However, no assumption is made about the kind of parallelism to be used. Transputers, connection machines, farms of workstations, cellular neural networks, crays and other hardware paradigms of parallelism are used by the authors of this collection. The papers arise from the areas of parallel knowledge representation, neural modeling, parallel non-monotonic reasoning, search and partitioning, constraint satisfaction, theorem proving, parallel decision trees, parallel programming languages and low-level computer vision. The final paper is a report about applications of massive parallelism and aims to capture the spirit of a whole period of computing history.
โฆ Table of Contents
sdarticle01......Page 1
sdarticle02......Page 3
sdarticle03......Page 5
sdarticle04......Page 43
sdarticle05......Page 70
sdarticle06......Page 96
sdarticle07......Page 120
sdarticle08......Page 143
sdarticle09......Page 162
sdarticle10......Page 176
sdarticle11......Page 203
sdarticle12......Page 225
sdarticle13......Page 241
sdarticle14......Page 271
sdarticle15......Page 299
sdarticle16......Page 319
sdarticle17......Page 332
๐ SIMILAR VOLUMES
Parallel processing for A1 problems is of great current interest because of its potential for alleviating the computational demands of Al procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge represent
</header><div itemprop="description" class="collapsable text"><p>Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas
With the increasing availability of parallel machines and the raising of interest in large scale and real world applications, research on parallel processing for Artificial Intelligence (Al) is gaining greater importance in the computer science environment. Many applications have been implemented an
<span>This book includes reviewed papers by international scholars from the 2020 International Conference on Pattern Recognition and Artificial Intelligence (held online). The papers have been expanded to provide more details specifically for the book. It is geared to promote ongoing interest and un