1.

Record Nr.

UNINA9910299701203321

Autore

Kulkarni Anand Jayant

Titolo

Probability Collectives : A Distributed Multi-agent System Approach for Optimization / / by Anand Jayant Kulkarni, Kang Tai, Ajith Abraham

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015

ISBN

3-319-16000-1

Edizione

[1st ed. 2015.]

Descrizione fisica

1 online resource (162 p.)

Collana

Intelligent Systems Reference Library, , 1868-4394 ; ; 86

Disciplina

006.3

Soggetti

Computational intelligence

Artificial intelligence

Statistical physics

Dynamics

Computational Intelligence

Artificial Intelligence

Complex Systems

Statistical Physics and Dynamical Systems

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references at the end of each chapters.

Nota di contenuto

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.

Sommario/riassunto

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.