Titlebook: Computational Intelligence; Principles, Techniqu Amit Konar Textbook 2005 Springer-Verlag Berlin Heidelberg 2005 Multi-agent system.artific

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Machine Learning Using Fuzzy Petri Nets,ay be employed in complex decision-making and learning such as automated car driving in an accident-prone environment. The chapter also presented a new scheme for knowledge refinement by adaptation of weights in a fuzzy Petri net using a different form of Hebbian learning.

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Textbook 2005, precise and highly comprehensive style. The textbook addresses the fundamental aspects of fuzzy sets and logic, neural networks, evolutionary computing and belief networks. The application areas include fuzzy databases, fuzzy control, image understanding, expert systems, object recognition, crimin

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正式演說(shuō)

https://doi.org/10.1007/978-3-642-95696-6recognition. Finally, the chapter introduces fuzzy associative memory neural nets and outlines algorithms for pattern classification by the proposed neural nets. Concluding remarks are listed at the end of the chapter.

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Matrix elements for spherical Gaussians,ples of the Q-learning algorithm have been illustrated with the well-known grid-world problem of mobile robots. The convergence analysis of the Q-learning algorithm is presented, and the scope of extension of the Q-learning algorithm in multi-agent learning systems has been addressed at the end of the chapter.

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Bmd955

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