A Fuzzy Logic System for Bargaining in Information Markets
ACM Transactions on Intelligent Systems and Technology (TIST)
Buyer behavior adaptation based on a fuzzy logic controller and prediction techniques
Fuzzy Sets and Systems
Electronic Commerce Research and Applications
On the use of particle swarm optimization and Kernel density estimator in concurrent negotiations
Information Sciences: an International Journal
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Present and future Web business models involve the trading of information goods. Information marketplaces can be considered as places where users search and retrieve information goods. Such places appear to be very interesting information retrieval models. Furthermore, Software Agent technology could help users and providers to work in such open environments providing a variety of advantages. Users as well as information providers could be represented by intelligent agents that work autonomously. The representatives of users assume the role of information buyers while the representatives of information sources could be referred to as sellers. In this paper, we examine a scenario where agents representing entities involved in an information marketplace bargain over the prices of information goods. Bargaining originates in Game Theory (GT). The rationale is that some entities contest to gain as much profit as possible in an open environment. We study the sellers’ side. Sellers involved in a number of games with buyers, are trying to achieve as greater prices as possible in order to gain more profit from each game. We present a theoretical model of deadline computation for which sellers are participating in the game. Over this time limit it is useless for sellers to continue the game while buyers reject the proposed prices.