Reputation in Artificial Societies: Social Beliefs for Social Order
Reputation in Artificial Societies: Social Beliefs for Social Order
Trust in Distributed Artificial Intelligence
MAAMAW '92 Selected papers from the 4th European Workshop on on Modelling Autonomous Agents in a Multi-Agent World, Artificial Social Systems
A Social Mechanism of Reputation Management in Electronic Communities
CIA '00 Proceedings of the 4th International Workshop on Cooperative Information Agents IV, The Future of Information Agents in Cyberspace
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Building trust in online auction markets through an economic incentive mechanism
Decision Support Systems
Supporting Trust in Virtual Communities
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 6 - Volume 6
Principles of Trust for MAS: Cognitive Anatomy, Social Importance, and Quantification
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
Believing Others: Pros and Cons
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Convergence of agent reputation with Alpha-Beta filtering vs. a fuzzy system
CIMCA '05 Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-1 (CIMCA-IAWTIC'06) - Volume 01
An integrated trust and reputation model for open multi-agent systems
Autonomous Agents and Multi-Agent Systems
Anticipatory Behavior in Adaptive Learning Systems: From Brains to Individual and Social Behavior
Anticipatory Behavior in Adaptive Learning Systems: From Brains to Individual and Social Behavior
Anticipations, Brains, Individual and Social Behavior: An Introduction to Anticipatory Systems
Anticipatory Behavior in Adaptive Learning Systems
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Competitive distributed systems pose a challenge to trust modeling due to the dynamic nature of these systems (e.g. electronic auctions) and the unreliability of self-interested agents. We propose a trust model which does not assume a concrete cognitive model for other agents that an agent may interact with, but uses the discrepancy between the information provided by other agents and its own experience in order to anticipate their actions. By anticipating the behavior of other agents, an agent is able to adapt more effectively to changes in the environment for its own benefit.