The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
Autonomy Oriented Computing: From Problem Solving to Complex Systems Modeling (Multiagent Systems, Artificial Societies, and Simulated Organizations)
Review on Computational Trust and Reputation Models
Artificial Intelligence Review
The Knowledge Engineering Review
Inferring binary trust relationships in Web-based social networks
ACM Transactions on Internet Technology (TOIT)
A survey of trust and reputation systems for online service provision
Decision Support Systems
Distributed task allocation in social networks
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Communications of the ACM - Web science
Learning task-specific trust decisions
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
An adaptive probabilistic trust model and its evaluation
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
ICNC '08 Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 01
CTO Roundtable: Cloud Computing
Communications of the ACM - A Blind Person's Interaction with Technology
Formal trust model for multiagent systems
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Power-Law Distributions in Empirical Data
SIAM Review
Autonomy-oriented computing (AOC): formulating computational systems with autonomous components
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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The problem of finding partners is concerned with how to identify some specific entities (agents) from a group that will be able to provide certain requested services. This problem can readily be found in applications such as file sharing and task allocation in open and/or distributed environments. Previous studies have shown that entities can effectively select their partners by means of evaluating their mutual trust relationships. Here a trust relationship between two entities refers to the establishment of one entity's belief that another entity will be able to accomplish a service of interest. In this work, we aim to study how the partner-finding problem can be more effectively and efficiently solved by allowing entities to autonomously update their beliefs and hence trust relationships based on their past experiences. In doing so, we introduce the notion of a trust network in which nodes correspond to entities and links represent trust relationships between entities. We apply the methodology of Autonomy-Oriented Computing (AOC) to model and simulate the behavior-based trust relationship updates of entities over time, as well as the structural characteristics of the trust network as being established by entities. Besides providing detailed formulations, we perform a series of experiments to evaluate the impacts of the proposed trust relationship update mechanism on the performance of partner finding.