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Probability Collectives A Distributed Multi-agent System Approach for Optimization /

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 techniqu...

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Hlavní autoři: Kulkarni, Anand Jayant. (Autor, http://id.loc.gov/vocabulary/relators/aut), Tai, Kang. (http://id.loc.gov/vocabulary/relators/aut), Abraham, Ajith. (http://id.loc.gov/vocabulary/relators/aut)
Korporativní autor: SpringerLink (Online service)
Médium: Elektronický zdroj E-kniha
Jazyk:English
Vydáno: Cham : Springer International Publishing : Imprint: Springer, 2015.
Vydání:1st ed. 2015.
Edice:Intelligent Systems Reference Library, 86
Témata:
Computational intelligence.
Artificial intelligence.
Statistical physics.
Dynamical systems.
Computational Intelligence.
Artificial Intelligence.
Complex Systems.
Statistical Physics and Dynamical Systems.
On-line přístup:https://doi.org/10.1007/978-3-319-16000-9
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Obsah:
  • 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.

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