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Probability collectives[electronic resource] :a distributed multi-agent system approach for optimization /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.3
書名/作者:	Probability collectives : a distributed multi-agent system approach for optimization // by Anand Jayant Kulkarni, Kang Tai, Ajith Abraham.
作者:	Kulkarni, Anand Jayant.
其他作者:	Abraham, Ajith.
出版者:	Cham : : Springer International Publishing :, 2015.
面頁冊數:	ix, 157 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Multiagent systems.
標題:	Artificial intelligence.
標題:	Computational intelligence.
標題:	Engineering.
標題:	Computational Intelligence.
標題:	Artificial Intelligence (incl. Robotics).
標題:	Statistical Physics, Dynamical Systems and Complexity.
ISBN:	9783319160009 (electronic bk.)
ISBN:	9783319159997 (paper)
內容註:	Introduction to Optimization -- Probability Collectives: A Distributed Optimization Approach -- Constrained Probability Collectives: A Heuristic Approach -- Constrained Probability Collectives with a Penalty Function Approach -- Constrained Probability Collectives With Feasibility-Based Rule I -- Probability Collectives for Discrete and Mixed Variable Problems -- Probability Collectives with Feasibility-Based Rule II.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-16000-9

Probability collectives[electronic resource] :a distributed multi-agent system approach for optimization /
Kulkarni, Anand Jayant.

Probability collectivesa distributed multi-agent system approach for optimization /[electronic resource] :by Anand Jayant Kulkarni, Kang Tai, Ajith Abraham. - Cham :Springer International Publishing :2015. - ix, 157 p. :ill., digital ;24 cm. - Intelligent systems reference library,v.861868-4394 ;. - Intelligent systems reference library ;v.24..

Introduction to Optimization -- Probability Collectives: A Distributed Optimization Approach -- Constrained Probability Collectives: A Heuristic Approach -- Constrained Probability Collectives with a Penalty Function Approach -- Constrained Probability Collectives With Feasibility-Based Rule I -- Probability Collectives for Discrete and Mixed Variable Problems -- Probability Collectives with Feasibility-Based Rule II.

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.

ISBN: 9783319160009 (electronic bk.)

Standard No.: 10.1007/978-3-319-16000-9doiSubjects--Topical Terms:

465477
Multiagent systems.

LC Class. No.: QA76.76.I58

Dewey Class. No.: 006.3

Probability collectives[electronic resource] :a distributed multi-agent system approach for optimization /
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