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Artificial intelligence and soft computing by Amit Konar PDF

By Amit Konar

ISBN-10: 0849313856

ISBN-13: 9780849313851

With all of the fabric on hand within the box of synthetic intelligence (AI) and smooth computing-texts, monographs, and magazine articles-there continues to be a major hole within the literature. beforehand, there was no complete source available to a wide viewers but containing a intensity and breadth of data that permits the reader to completely comprehend and without difficulty practice AI and delicate computing concepts.Artificial Intelligence and smooth Computing fills this hole. It offers either the normal and the fashionable features of AI and gentle computing in a transparent, insightful, and hugely finished sort. It offers an in-depth research of mathematical versions and algorithms and demonstrates their functions in genuine international difficulties. starting with the behavioral point of view of "human cognition," the textual content covers the instruments and strategies required for its clever recognition on machines. the writer addresses the classical aspects-search, symbolic common sense, making plans, and laptop learning-in element and comprises the most recent examine in those components. He introduces the trendy elements of sentimental computing from first rules and discusses them in a fashion that allows a newbie to understand the topic. He additionally covers a few different best features of AI study, together with nonmonotonic and spatio-temporal reasoning, wisdom acquisition, and lots more and plenty extra. synthetic Intelligence and gentle Computing: Behavioral and Cognitive Modeling of the Human mind is exclusive for its different content material, transparent presentation, and total completeness. It offers a pragmatic, precise advent that may turn out worthwhile to desktop technology practitioners and scholars in addition to to researchers migrating to the topic from different disciplines.

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6: A semantic net representation of "birds". Planning: Another significant area of AI is planning. The problems of reasoning and planning share many common issues, but have a basic difference that originates from their definitions. The reasoning problem is mainly concerned with the testing of the satisfiability of a goal from a given set of data and knowledge. The planning problem, on the other hand, deals with the determination of the methodology by which a successful goal can be achieved from the known initial states [1].

22, 1984. , Genetic algorithms + Data Structures = Evolution Programs, Springer-Verlag, Berlin, 1992. , Yamada, S. I. , “High speed CAM-based architecture for a PROLOG machine,” IEEE Trans. on Computers, vol. 37, no. 11, November 1997. [25] Narendra, K. S. , "Identification and control of dynamical system using neural networks,” IEEE Trans. on Neural Networks, vol. 1. , pp. 4-27, 1990. , Zhang, L. , “Adaptive Evolutionary Planner/Navigator for Mobile Robots,” IEEE Trans. on Evolutionary Computation, vol.

Planning routes through uncertain territory,” Artificial Intelligence, vol. 22, 1984. , Genetic algorithms + Data Structures = Evolution Programs, Springer-Verlag, Berlin, 1992. , Yamada, S. I. , “High speed CAM-based architecture for a PROLOG machine,” IEEE Trans. on Computers, vol. 37, no. 11, November 1997. [25] Narendra, K. S. , "Identification and control of dynamical system using neural networks,” IEEE Trans. on Neural Networks, vol. 1. , pp. 4-27, 1990. , Zhang, L. , “Adaptive Evolutionary Planner/Navigator for Mobile Robots,” IEEE Trans.

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Artificial intelligence and soft computing by Amit Konar


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