This book provides an emerging computational intelligence tool in the framework of collective intelligence for modeling and controlling distributed multi-agent systems referred to as Probability Collectives. In the modified Probability Collectives methodology a number of constraint handling techniques are incorporated, which also reduces the computational complexity and improved the convergence and efficiency. Numerous examples and real world problems are used for illustration, which may also allow the reader to gain further insight into the associated concepts.
Publisher: Springer International Publishing AG
Number of pages: 157
Weight: 2642 g
Dimensions: 235 x 155 x 9 mm
Edition: Softcover reprint of the original 1st ed. 201
"The book contains numerous overviews of the optimization literature, and each chapter has a comprehensive bibliography. The book will be of interest to both students who are interested in optimization and practitioners." (J. P. E. Hodgson, Computing Reviews, June, 2015)
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