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Dynamic, Genetic, and Chaotic Programming
註釋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that has previously been scattered worldwide over a number of publications and research reports--as well as previously unpublished methods and results from the IRIS (Integration of Reasoning, Informing and Serving) Group.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.