Paper Info
Title
Asymptotic analysis of computational multi-agent systems
Abstract
A stationary Markov chain model of the agent-based computation system EMAS is presented. The primary goal of the model is better understanding the behavior of this class of systems as well as their constraints. The ergodicity of this chain can be verified for the particular case of EMAS, thus implying an asymptotic guarantee of success (the ability of finding all solutions of the global optimization problem). The presented model may be further adapted to numerous evolutionary and memetic systems.
Year
DOI
Venue
2010
10.1007/978-3-642-15844-5_48
PPSN (1)
Keywords
Field
DocType
computational multi-agent system,asymptotic analysis,particular case,stationary markov chain model,global optimization problem,primary goal,asymptotic guarantee,agent-based computation system,memetic system,global optimization,multi agent system,markov chain model
Memetic algorithm,Ergodicity,Mathematical optimization,Computer science,Markov chain,Multi-agent system,Asymptotic analysis,Global optimization problem,Computation
Conference
Volume
ISSN
ISBN
6238
0302-9743
3-642-15843-9
Citations 
PageRank 
References 
2
0.38
10
Authors
4
Name
Order
Citations
PageRank
Aleksander Byrski126945.03
Robert Schaefer210110.99
Maciej Smołka310713.60
Carlos Cotta441644.36