Parallel Processing for Artificial Intelligence (Machine Intelligence & Pattern Recognition) (v. 3)

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. The third in an informal series of books about parallel processing for Artificial Intelligence, this volume 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 an experience report about applications of massive parallelism which can be said to capture the spirit of a whole period of computing history.

This volume provides the reader with a snapshot of the state of the art in Parallel Processing for Artificial Intelligence. The third in an informal series of books about parallel processing for Artificial Intelligence, this volume 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 an experience report about applications of massive parallelism which can be said to capture the spirit of a whole period of computing history. This volume provides the reader with a snapshot of the state of the art in Parallel Processing for Artificial Intelligence 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 This volume provides the reader with a snapshot of the state-of-the-art in parallel processing. The papers presented arise from such areas as: parallel knowledge representation; neural modeling; parallel non-monotonic reasoning; search and partitioning and constraint satisfaction.