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Parallelism, Learning, Evolution Lecture Notes in Artificial Intelligence

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Parallelism, Learning, Evolution Lecture Notes in Artificial Intelligence Synopsis

This volume presents the proceedings of a workshop on evolutionary models and strategies and another workshop on parallel processing, logic, organization, and technology, both held in Germany in 1989. In the search for new concepts relevant for parallel and distributed processing, the workshop on parallel processing included papers on aspects of space and time, representations of systems, non-Boolean logics, metrics, dynamics and structure, and superposition and uncertainties.

The point was stressed that distributed representations of information may share features with quantum physics, such as the superposition principle and the uncertainty relations. Much of the volume contains material on general parallel processing machines, neural networks, and system-theoretic aspects. The material on evolutionary strategies is included because these strategies will yield important and powerful applications for parallel processing machines, and open the wayto new problem classes to be treated by computers.

About This Edition

ISBN: 9783540550273
Publication date:
Author: JD Becker, I Eisele, FW Mündemann
Publisher: Springer an imprint of Springer Berlin Heidelberg
Format: Paperback
Pagination: 530 pages
Series: Lecture Notes in Computer Science
Genres: Systems analysis and design
Condensed matter physics (liquid state and solid state physics)
Materials science
Mathematical theory of computation
Computer architecture and logic design
Artificial intelligence

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