Language:
English
繁體中文
Help
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Probability collectives = a distribu...
~
SpringerLink (Online service)
Probability collectives = a distributed multi-agent system approach for optimization /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Probability collectives/ by Anand Jayant Kulkarni, Kang Tai, Ajith Abraham.
Reminder of title:
a distributed multi-agent system approach for optimization /
Author:
Kulkarni, Anand Jayant.
other author:
Tai, Kang.
Published:
Cham :Springer International Publishing : : 2015.,
Description:
ix, 157 p. :ill., digital ; : 24 cm.;
Contained By:
Springer eBooks
Subject:
Multiagent systems. -
Online resource:
http://dx.doi.org/10.1007/978-3-319-16000-9
ISBN:
9783319160009 (electronic bk.)
Probability collectives = a distributed multi-agent system approach for optimization /
Kulkarni, Anand Jayant.
Probability collectives
a 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. 3..
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:
745736
Multiagent systems.
LC Class. No.: QA76.76.I58
Dewey Class. No.: 006.3
Probability collectives = a distributed multi-agent system approach for optimization /
LDR
:02048nam a2200325 a 4500
001
836415
003
DE-He213
005
20150921113945.0
006
m d
007
cr nn 008maaau
008
160421s2015 gw s 0 eng d
020
$a
9783319160009 (electronic bk.)
020
$a
9783319159997 (paper)
024
7
$a
10.1007/978-3-319-16000-9
$2
doi
035
$a
978-3-319-16000-9
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.76.I58
072
7
$a
UYQ
$2
bicssc
072
7
$a
COM004000
$2
bisacsh
082
0 4
$a
006.3
$2
23
090
$a
QA76.76.I58
$b
K96 2015
100
1
$a
Kulkarni, Anand Jayant.
$3
1066528
245
1 0
$a
Probability collectives
$h
[electronic resource] :
$b
a distributed multi-agent system approach for optimization /
$c
by Anand Jayant Kulkarni, Kang Tai, Ajith Abraham.
260
$a
Cham :
$c
2015.
$b
Springer International Publishing :
$b
Imprint: Springer,
300
$a
ix, 157 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Intelligent systems reference library,
$x
1868-4394 ;
$v
v.86
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.
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.
650
0
$a
Multiagent systems.
$3
745736
650
0
$a
Artificial intelligence.
$3
559380
650
0
$a
Computational intelligence.
$3
568984
650
1 4
$a
Engineering.
$3
561152
650
2 4
$a
Computational Intelligence.
$3
768837
650
2 4
$a
Artificial Intelligence (incl. Robotics).
$3
682894
650
2 4
$a
Statistical Physics, Dynamical Systems and Complexity.
$3
769149
700
1
$a
Tai, Kang.
$3
1066529
700
1
$a
Abraham, Ajith.
$3
670176
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer eBooks
830
0
$a
Intelligent systems reference library ;
$v
v. 3.
$3
775129
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-16000-9
950
$a
Engineering (Springer-11647)
based on 0 review(s)
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login