Extracting reputation in multi agent systems by means of social network topology

Abstract

The problem of calculating a degree of reputation for agents acting as assistants to the members of an electronic community is discussed and a solution presented. Usual reputation mechanisms rely on feedback after interaction between agents. An alternative way to establish reputation is related with the position of each member of a community within the corresponding social network. We propose a method based on this idea, which is also used by well-known ranking algorithms, discuss its properties as well as experimental results and compare them to other reputation mechanisms for electronic communities supported by agents. The method proposed uses only local information in order to extract reputation and it is able to adapt automatically to the topology of the network or graph.

Finding influential agent groups in complex multiagent software systems based on citation network analyses

“…For example, in [6], a model for decision making that can satisfy the social role of each agent is proposed, and such a method only considers an individual agent's role in the structure of the citation network. Pujol et al [27] considered the degree calculation of reputation for agents in an electronic community and presented a method for extracting reputation in multiagent systems by means of social network topology. Marshakova [11] presented co-citation analysis to build citation networks in information science and revealed the topical structure of information science, the communities of authors and the names of single leading scientists.…”

Peer profile based trust model for P2P systems using genetic algorithm

“…Marsh [24], Regret [25] and NodeRanking [26] are some of the social network based trust systems. Marsh was among the first to try to give a formal treatment of trust that could be used in computer science.…”

Using asymmetric keys in a certified trust model for multiagent systems

“…the trust of a society about something or someone, then we name this phenomenon as Reputation (Pujol, Sangesa, & Delgado, 2002). Ramchurn et al (2004) enrich this definition by asserting that trust can be ''derived from the aggregation of opinions present in a community".…”