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 pop
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.
Our site uses cookies and similar technologies to offer you a better experience. We use analytical cookies (our own and third party) to understand and improve your browsing experience, and advertising cookies (our own and third party) to send you advertisements in line with your preferences. To modify or opt-out of the use of some or all of our cookies, please go to “Manage Cookies” or view our Cookie Policy to find out more. By clicking “Accept all” you consent to the use of these cookies.