On the Use of Fuzzy Logic in a Seller Bargaining Game Kostas Kolomvatsos, Christos Anagnostopoulos, and Stathes Hadjiefthymiades Pervasive Computing Research Group, Department of Informatics and Telecommunications, University of Athens, Panepistimiopolis, Ilissia, Athens, 15784, tel:+302107275127 e-mails: {kostasks, bleu, shadj}@di.uoa.gr Abstract Information marketplaces are places where users search and retrieve information goods. Intelligent Agents could represent the participating entities in such places, i.e, assume the role of buyers and sellers of information products. In this paper, we introduce a finite horizon bargaining model between buyers and sellers. We examine the seller’s side and define a method for the ‘bargaining’ deadline calculation based on Fuzzy-Logic (FL). Such deadline indicates the time for which it is profitable for a seller to participate in the bargaining procedure, i.e., the time threshold for his offers. We represent the seller’s knowledge / policy adopting the Fuzzy Set Theory and provide a fuzzy inference engine for reasoning about the bargaining deadline. The result of the reasoning process defines the degree of patience of the seller agent, thus, affecting the time for which that seller participates in the bargaining game. 1. Introduction With the rapid development of the Web, information has become the most important trading commodity in modern societies [1]. A huge amount of information sources are available to users. Simultaneously, due to the abundance of information sources, finding information becomes a demanding procedure. Users have to browse and process numerous sources in order to find the information that best meets to their interests. Intelligent Agents could be a solution to the above problem. Agents are software or hardware components capable of acting exactingly in order to accomplish tasks on behalf of their owners [2]. Their intelligence mostly refers to their capability to learn the preferences of their owners, thus, increases their performance. Hence, agents can undertake the responsibility of finding information in the Web with the minimum intervention by users. Information Markets (IMs), could provide a place where autonomous entities representing users try to locate the desired information products. In IMs, participants negotiate for the exchange of information commodities. Usually, there are two main groups of participants: the buyers and the sellers. However, in IMs, an additional group of entities may be responsible for administration or mediation tasks facilitating buyers and sellers in their negotiation. The combination of the technologies of agents and IMs is highly advantageous for the information discovery and acquisition processes. Agents represent users in an IM, where there are sellers that offer information goods. We study the combination of the Intelligent Agent and IM technologies and present a buyer-seller interaction model. The objective of our work is to define an economic model for the IM organisation. Our model enables the engineering of algorithms and protocols for more efficient transactions. This model is based on Game Theory (GT) [3]. GT provides an efficient way to describe interactions between entities that try to maximize their profits. A methodology that could offer a number of advantages in interaction models is Fuzzy Logic theory. Fuzzy Sets [4] can be seen as an extension of the Boolean set theory. Fuzzy Logic (FL) is an algebra based on fuzzy sets and provides reasoning mechanisms that are approximate rather than precise. FL deals with ambiguous information and helps at representing the knowledge of the agents involved in an IM in order to automatically assume decisions during the bargaining process. An important decision is the calculation of the correct time for which an agent will participate in the game. The calculation of that deadline affects the behaviour of a seller concerning the proposed prices. We adopt FL for: (i) representing the seller-expert knowledge, and (ii) inferring the Annual IEEE International Computer Software and Applications Conference 0730-3157/08 $25.00 © 2008 IEEE DOI 184 Annual IEEE International Computer Software and Applications Conference 0730-3157/08 $25.00 © 2008 IEEE DOI 10.1109/COMPSAC.2008.172 184 Annual IEEE International Computer Software and Applications Conference 0730-3157/08 $25.00 © 2008 IEEE DOI 10.1109/COMPSAC.2008.172 184