|
|
|
|
LEADER |
02315nmm a2200373 u 4500 |
001 |
EB000945444 |
003 |
EBX01000000000000000739034 |
005 |
00000000000000.0 |
007 |
cr||||||||||||||||||||| |
008 |
150302 ||| eng |
020 |
|
|
|a 9783319160009
|
100 |
1 |
|
|a Kulkarni, Anand Jayant
|
245 |
0 |
0 |
|a Probability Collectives
|h Elektronische Ressource
|b A Distributed Multi-agent System Approach for Optimization
|c by Anand Jayant Kulkarni, Kang Tai, Ajith Abraham
|
250 |
|
|
|a 1st ed. 2015
|
260 |
|
|
|a Cham
|b Springer International Publishing
|c 2015, 2015
|
300 |
|
|
|a IX, 157 p. 68 illus
|b online resource
|
505 |
0 |
|
|a 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.
|
653 |
|
|
|a Complex Systems
|
653 |
|
|
|a Computational intelligence
|
653 |
|
|
|a Artificial Intelligence
|
653 |
|
|
|a Computational Intelligence
|
653 |
|
|
|a System theory
|
653 |
|
|
|a Artificial intelligence
|
653 |
|
|
|a Mathematical physics
|
653 |
|
|
|a Theoretical, Mathematical and Computational Physics
|
700 |
1 |
|
|a Tai, Kang
|e [author]
|
700 |
1 |
|
|a Abraham, Ajith
|e [author]
|
041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
989 |
|
|
|b Springer
|a Springer eBooks 2005-
|
490 |
0 |
|
|a Intelligent Systems Reference Library
|
028 |
5 |
0 |
|a 10.1007/978-3-319-16000-9
|
856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-319-16000-9?nosfx=y
|x Verlag
|3 Volltext
|
082 |
0 |
|
|a 006.3
|
520 |
|
|
|a 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
|