A Fuzzy Logic System for Bargaining in Information Markets
ACM Transactions on Intelligent Systems and Technology (TIST)
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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The information from Internet and the acceptance of offers are uncertainty in e-commerce, so this work presents a model using fuzzy logic to support bilateral agent negotiation. In the model, a negotiation can be made only if there exits a zone of agreement between the retentive offers of participants. We assigned approximate weight to different issues of an offer based on their importance degrees and calculated aggregated satisfaction value of the offer to make a decision. We used three different concession strategies to get a counter offer. A better performance is obtained from negotiators’ exchanged offers after analyzing experimental results. The presented negotiation agent model is more effective than human negotiation and makes negotiators achieve mutual benefits.