An Analysis of Efficiency on Multi agent Systems with Symbiotic Learning and EvolutionMd. Tofazzal Hossain1* and Kotaro Hirasawa2
- Corresponding Author:
- Md. Tofazzal Hossain
Kangawaken, Kawasaki Shi, Asao-ku
Takaishi, 4-22-2-503, Japan, 215-0003
E-mail: [email protected]
Received date: July 10, 2015; Accepted date: October 13, 2015; Published date: October 19, 2015
Citation: Hossain MT, Hirasawa K (2015) An Analysis of Efficiency on Multiagent Systems with Symbiotic Learning and Evolution. Int J Swarm Intel Evol Comput 4:122. doi:10.4172/2090-4908.1000122
Copyright: © 2015 Hossain MT, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Masbiole (Multiagent Systems with Symbiotic Learning and Evolution) is a new methodology in conventional Multiagent Systems (MASs). In Masbiole, agents evolve considering not only their own benefits and losses, but also the benefits and losses of opponent agents. As a result, Masbiole can escape from Nash Equilibria and obtain better performances than conventional MASs. On the other hand, a newly developed evolutionary computing technique called Genetic Network Programming (GNP) which has the directed graph-type gene structure can develop and design the required intelligence mechanism for agents. As a result, GNP is considered to be well-suited for optimization problems in agents of MASs. Therefore, in this study, a test bed negotiation model is proposed using the evolutionary method of Masbiole as well as the evolutionary method of GNP, with the aim to study the effectiveness and efficiency of Masbiole in dynamic problems. The results obtained by the symbiotic evolution of the Masbiole systems are compared with those obtained by the GNP evolution.