Enhanced Reputation Model with Forgiveness for E-Business Agents

Abstract

Trust is a very important quality attribute of an e-service. In particular, the increasing complexity of the e-business environment requires the development of new computational models of trust and reputation for e-business agents. In this paper, the authors introduce a new reputation model for agents engaged in e-business transactions. The model enhances classic reputation models by the addition of forgiveness factor and the use of new sources of reputation information based on agents groups. The paper proposes an improvement of this model by employing the recent con-resistance concept. Finally, the authors show how the model can be used in an agent-based market environment where trusted buyer and seller agents meet, negotiate, and transact multi-issue e-business contracts. The system was implemented using JADE multi-agent platform and initially evaluated on a sample set of scenarios. The paper introduces the design and implementation of the agent-based system together with the experimental scenarios and results.

Psychology-Inspired Trust Restoration Framework in Distributed Multiagent Systems

“…In this study, forgiveness and regret are considered as implementable properties for formalizing the incorporation of trust defining a computational model. Forgiveness, in particular, has been extensively studied as a positive method of coping with trust violations in [12,[20][21][22][23][24][25][26][27], while regret, always together with responsibility, is used to form the definition of an apology [13,20,21,[28][29][30][31]. For instance, an apology was defined by [20] as "a decisive public expression regarding both responsibility and regret for a violation of trust."…”