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
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A survey of trust and reputation systems for online service provision
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Learning task-specific trust decisions
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LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part II
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The problem of finding partners is to identify which entities (agents) can provide requested services from a group of entities. It can be found in open and distributed environments for such tasks as file sharing and resource allocation. Previous studies have shown that entities can refine and determine partners through measuring trust relationships, i.e., the beliefs of entities that others will accomplish a request for assigned services at hand. Entities dynamically change their beliefs through recalling their past experiences in order to quickly identify partners for new requests. This paper aims to observe whether those changes can enable entities efficiently find partners and hence provide services. To this end, we propose a dynamic network of trust-based entities. Then, we investigate the dynamics of its structure and efficiency in the above-mentioned aspects. Autonomy-Oriented Computing (AOC) is applied to observe how the dynamics emerge from local behaviors. A notion of autonomy is embodied in defining how entities activate their partner finding behaviors, whereas self-organization is realized to update the strength of trust relationships. Experimental results explicitly display a dynamic process of this network, changing from containing no link (trust relationship) to having some stable links. Specially, in this process, the efficiency gradually gets enhanced.