A Social Mechanism of Reputation Management in Electronic Communities

Yu, Bin; Singh, Munindar P.

doi:10.1007/978-3-540-45012-2_15

Cited by 295 publications

(212 citation statements)

References 4 publications

Supporting

Mentioning

207

Contrasting

Unclassified

Order By: Relevance

“…Each agent maintains DIT i,j (t) variables for the agents with which they have had direct interactions. We used the following trust updating scheme motivated by that described in [16]: …”

Section: Direct Interaction Trust (Dit)mentioning

confidence: 99%

“…The system takes into account three different sources of information: direct experiences, information from third party agents and social structures. Yu and Singh [16] developed an approach for social reputation management, in which they represented an agent's ratings regarding another agent as a scalar and combined them with testimonies using combination schemes similar to certainty factors. Huynh et al [4] introduced a trust and reputation model called FIRE that incorporates interaction trust, role-based trust, witness reputation, and certified reputation to provide a trust metric.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

On the Impact of Witness-Based Collusion in Agent Societies

Salehi‐Abari

White

2009

Principles of Practice in Multi-Agent Systems

View full text Add to dashboard Cite

Abstract. In ways analogous to humans, autonomous agents require trust and reputation concepts in order to identify communities of agents with which to interact reliably. This paper defines a class of attacks called witness-based collusion attacks designed to exploit trust and reputation models. Empirical results demonstrate that unidimensional trust models are vulnerable to witness-based collusion attacks in ways independent multidimensional trust models are not. This paper analyzes the impact of the proportion of witness-based colluding agents on the society. Furthermore, it demonstrates that here is a need for witness interaction trust to detect colluding agents in addition to the need for direct interaction trust to detect malicious agents. By proposing a set of policies, the paper demonstrates how learning agents can decrease the level of encounter risk in a witness-based collusive society.

show abstract

“…Each agent maintains DIT i,j (t) variables for the agents with which they have had direct interactions. We used the following trust updating scheme motivated by that described in [16]: …”

Section: Direct Interaction Trust (Dit)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the Impact of Witness-Based Collusion in Agent Societies

Salehi‐Abari

White

2009

Principles of Practice in Multi-Agent Systems

View full text Add to dashboard Cite

show abstract

“…This trust model [21] uses Dempster-Shafer theory of evidence to aggregate recommendations from different witnesses. The main characteristic of this model is the relative importance of fails over success.…”

Section: Related Workmentioning

confidence: 99%

Analysis of the Agent Reputation and Trust Testbed

Gómez¹,

Sabater-Mir²,

Carbó³

et al. 2008

Int. Artif.

View full text Add to dashboard Cite

Trust modelling is a challenging issue due to the dynamic nature of distributed systems and the unreliability of self-interested agents. In this context, the Agent Reputation and Trust (ART) Testbed has been used to compare trust models in two Spanish competitions in 2006 and 2007 and several international competitions. In this paper we describe the model we have presented to the Spanish competitions. We propose a trust model that uses the discrepancy between the information provided by other agents and its own experience in order to anticipate their actions, instead of using that discrepancy as a source of dishonesty and distrust. In addition we propose a cognitive model based on motivational attitudes to implement adaptive behaviors. Various implementations of this trust model have participated in the competitions; one was the winner of the first Spanish competition in 2006, the other won a combined game that included the participants in the two Spanish competitions.

show abstract

“…Before that, they implemented a relevant computational method in the Social Interaction FrameWork (SIF) [13] in which an agent evaluated the reputation of another agent on the basis of direct observation and through other witnesses. The idea of using the opinion of other agents to build a reputation is also applied by Yu and Singh [21]. Their agents build and manage the trust representations not only taking into account the previous experiences of their users, but also communicating with other agents (belonging to other users).…”

Section: Related Workmentioning

confidence: 99%

Opinion-Based Filtering through Trust

Montaner

López

Rosa

2002

Cooperative Information Agents VI

View full text Add to dashboard Cite

Abstract. Recommender systems help users to identify particular items that best match their tastes or preferences. When we apply the agent theory to this domain, a standard centralized recommender system becomes a distributed world of recommender agents. Therefore, due to the agent's world, a new information filtering method appears: the opinion-based filtering method. Its main idea is to consider other agents as personal entities which you can rely on or not. Recommender agents can ask their reliable friends for an opinion about a particular item and filter large sets of items based on it. Reliability is expressed through a trust value with which each agent labels its neighbors. Thus, the opinion-based filtering method needs a model of trust in the collaborative world. The model proposed emphasizes proactiveness since the agent looks for other agents in a situation of lack of information instead of remaining passive or providing either a negative or empty answer to the user. Finally, our social model of trust exploits interactiveness while preserving privacy.

show abstract

A Social Mechanism of Reputation Management in Electronic Communities

Cited by 295 publications

References 4 publications

On the Impact of Witness-Based Collusion in Agent Societies

On the Impact of Witness-Based Collusion in Agent Societies

Analysis of the Agent Reputation and Trust Testbed

Opinion-Based Filtering through Trust

Contact Info

Product

Resources

About