Stroke economy approach for constructing complex expert system using multi agent architecture.
| ||International Journal of Computer Trends and Technology (IJCTT)|| |
|© May to June Issue 2011 by IJCTT Journal|
|Volume-1 Issue-2 |
|Year of Publication : 2011|
|Authors : U.Chandrasekhar , S.Sahithya.|
Mohammed Ali Hussain, Dr. K.V.Sambasiva Rao. "Stroke economy approach for constructing complex expert system using multi agent architecture."International Journal of Computer Trends and Technology (IJCTT),V1(2):190-194 May to June Issue 2011 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract—In a highly competitive and ever evolving dynamic environment the need for an effective and a highly efficient work force that can reduce various overheads , is massive. This is where a distributed, multi agent architecture comes into play. In th is paper, we propose a decentralized, multi agent architecture that works in a distributed and dynamic environment . It uses stroke economy approach to optimize itself and evolve into an expert system of experts . The aim is to construct a unified mind from several minds, each exp ert in a sub domain. The goal is to achieve variety in task handling approaches and quality output, while optimizing task scheduling process. We also present a learning mechanism which helps individual agents to lift themselves up to the le vel of more expe rienced agents, i n their sub domain. We also aim to minimize the size of system , initially commissioned for that application , optimize transfer of data and schedule tasks effectively , promising a high quality performance
 Mark Humphrys and Ciaran O’Leary, “Constructing complex minds through multiple authors”, 7tn International conference, SAB’02, August - 2002
 Munir Merdan, Vedran Kordic, Alois Zoitl & Aleksandar Lazinica,"Knowledge - based Multi - agent Architecture", IEEE (CIMCA - IAWTIC`06) .
 D. Vallejo, J.Albusac, J.J.Castro - Schez, C.Glez - Morcillo, L.Jime ´nez, "A multi - agent architecture for supporting distributed normality - based Intelligent surveillance", Engineering Applications of Artificial Intelligen ce 24(2011)325 – 340 .
 Yuanda Cao,Nutao Jiang, Qing Zhou, "A Distributed Multi - agent Cooperative Expert System Tool",Proceedings of I C SP `98 .
 Ming Tan, “Multi - Agent Reinforcement Learning: Independent vs. Cooperative Agents”, Proceedings of 10 th International Conference on Machine Learning. 330 - 337 .
 Jyi - Shane Liu, Katia P.Sycara, “Multiagent Coordination in Tightly Coupled Task Scheduling”, Proceedings of 1 st International conference on Multi Agent systems, 1996. American Association for AI , 181 - 188
Keywords— Multi agent architectur e , Distributed AI, Subsumption architecture , Reinforcement learning