DocumentCode
2270698
Title
Believing others: pro and cons
Author
Sen, Sandip ; Biswas, Anish ; Debnath, Sandip
Author_Institution
Dept. of Math. & Comput. Sci., Tulsa Univ., OK, USA
fYear
2000
fDate
2000
Firstpage
279
Lastpage
285
Abstract
Under the assumption that agents remain in the system for significant time periods, or that the agent composition changes only slowly Sen (1996) has previously presented a prescriptive strategy for promoting and sustaining cooperation among self-interested agents. The adaptive, probabilistic policy prescribed promotes reciprocative cooperation that improves both individual and group performance in the long run. In the short run, however, selfish agents could still exploit reciprocative agents. In this paper we evaluate the hypothesis that the exploitative tendencies of selfish agents can be effectively curbed if reciprocative agents share their “opinions” of other agents. Since the true nature of agents are not known a priori and is learned from experience, believing others can also pose other hazards. We provide a learned trust-based evaluation function that is shown to resist both individual and concerted deception on the part of selfish agents
Keywords
belief maintenance; learning by example; multi-agent systems; probability; belief maintenance; learning from experience; multiple agent systems; prescriptive strategy; probability; reciprocative cooperation; selfish agents; Centralized control; Cost accounting; Electronic commerce; Environmental economics; Hazards; Humans; Open systems; Problem-solving; Recommender systems; Resists;
fLanguage
English
Publisher
ieee
Conference_Titel
MultiAgent Systems, 2000. Proceedings. Fourth International Conference on
Conference_Location
Boston, MA
Print_ISBN
0-7695-0625-9
Type
conf
DOI
10.1109/ICMAS.2000.858464
Filename
858464
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