Agent negotiations for iImproving quality of solutions from multiple perspectives

Abstract

-Most of the real world problems can be solved using more than one method which may return slightly different solutions. For instance, statistical techniques artificial neural networks, fuzzy logic and genetic algorithm can model the same real world problem subject to own strengths and weaknesses. However, it is evident that human beings can modify improve solutions generated in the individual capacity through negotiations among the individuals. This concept has been employed in the Multi Agent Systems (MAS) technology which can model complex real world problems to achieve quality solutions beyond the individual capacity. In this work, MAS has been used to ensemble weather forecasting results individually generated by Artificial Neural Network (ANN) and Genetic Algorithms (GA) through negotiation among solutions. It considers ANN and GA ab two agents. It has selected this application domain to demonstrate the concept since weather forecasting is important for many sectors such as agriculture, fisheries and transportation. Our MAS solution forecasts the rainfall for next twenty four hours with the use of set of present weather conditions as inputs for ANN and GA agents. The defied two agents arc used to operate on an ANN and GA solutions that start negotiation & deliberation to produce a more rational forecasting. The experiment concludes that even when solutions by ANN Agent and GA agent shows a disparity at the beginning, they reach to commonly agreeable solution through the negotiation in the multi agent solution with a 65% of success.