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Can I read Parallel Processing for Artificial Intelligence (Machine Intelligence & Pattern Recognition) (v. 3) on EtoBox?

Parallel Processing for Artificial Intelligence (Machine Intelligence & Pattern Recognition) (v. 3) by James Geller, Hiroaki Kitano and Christian B. Suttner (Eds.) is a nonfiction available to read on EtoBox.

What is Parallel Processing for Artificial Intelligence (Machine Intelligence & Pattern Recognition) (v. 3) about?

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.

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

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
James Geller, Hiroaki Kitano and Christian B. Suttner (Eds.)
Publisher
Academic Press, Elsevier
Published
1997
Language
EN
ISBN
9780444824868
Category
nonfiction
Subjects
Computer Science, Stem

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