Dynamic, genetic, and chaotic programming : the sixth generation /

Natural language, decision making, nonstationary environments, and other dynamic processes and systems represent some of the greatest challenges facing sixth generation computer technologies. Here, for the first time, is a practical software engineering and applications-oriented work that applies fi...

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Bibliographic Details
Corporate Author: IRIS Group
Other Authors: Souček, Branko
Format: Book
Language:English
Published: New York : Wiley, c1992
New York : [1992]
Series:Sixth-generation computer technology series
Sixth-generation computer technology series
Subjects:
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520 |a Natural language, decision making, nonstationary environments, and other dynamic processes and systems represent some of the greatest challenges facing sixth generation computer technologies. Here, for the first time, is a practical software engineering and applications-oriented work that applies five new neural, genetic, and chaotic paradigms--including the much heralded genetic programming--to a full range of dynamic processes and systems for engineers, designers, developers, and students alike. Each of the paradigms listed below is examined, described, tested, and compared using a range of examples and problems to highlight their unique features and uses: adaptive learning--reinforcement learning and recurrent neural networks; rule-based computing--automated knowledge acquisition; genetic algorithms--adaptation of strings of characters or blocks describing dynamic processes; genetic programming--adaptation of hierarchically structured computer programs; and software of chaos--nonlinear dynamics in the presence of strange attractors. The book presents a unified treatment of material that has previously been scattered worldwide over a number of publications and research reports--as well as previously unpublished methods and results from the IRIS (Integration of Reasoning, Informing and Serving) Group. Dynamic, Genetic, and Chaotic Programming: The Sixth Generation imitates organic evolutionary processes, parallelism, and collective learning paradigms of natural populations, and in this way offers new revolutionary methods for scientific and technical data processing 
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