Trust Management Through Fuzzy Reputation

Carbó, Javier; Molina, José M.; Dávila, Jorge

doi:10.1142/s0218843003000681

Cited by 126 publications

(67 citation statements)

References 12 publications

(10 reference statements)

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“…Another example of a socio-cognitive approach is the fuzzy reputation agent system (AFRAS) by Carbo et al [4], which supports the fuzzy nature of the reputation concept itself. It uses fuzzy logic to represent reputation since this concept is built up with vague evaluations (they depend on personal and subjective criteria), uncertain recommendations (malicious agents, different points of view), and incomplete information (untraceability of every agent in open systems).…”

Section: Related Workmentioning

confidence: 91%

Analysis of the Agent Reputation and Trust Testbed

Gómez¹,

Sabater-Mir²,

Carbó³

et al. 2008

Int. Artif.

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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.

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Section: Related Workmentioning

confidence: 91%

Analysis of the Agent Reputation and Trust Testbed

Gómez¹,

Sabater-Mir²,

Carbó³

et al. 2008

Int. Artif.

View full text Add to dashboard Cite

show abstract

“…This internal reasoning of agents has already been tested in adhoc simulations from different perspectives: the convergence of reputation (Carbo et al 2003), the influence of benevolent recommendations (Carbo et al 2005), and finally the dynamics of our system with a collusion of malicious providers and recommenders (Carbo et al 2007b). It has also been considered its application to generic electronic services in the book E-Service Intelligence-Methodologies, Technologies and Applications (Carbo et al 2007a) and it has been applied and compared with the web service provided by MovieLens Website in the International Journal of Web Engineering and Technology (Carbo and Molina 2004).…”

Section: A Fuzzy Reputation Model (Afras)mentioning

confidence: 99%

“…AFRAS (Carbo et al 2003) agent adopts a socio-cognitive approach to model trust and reputation of agents. AFRAS continuously updates human-like mental attributes, expressed in fuzzy terms to adjust their progressive and smooth adaptation to the situations faced.…”

Section: A Fuzzy Reputation Model (Afras)mentioning

confidence: 99%

An extension of a fuzzy reputation agent trust model (AFRAS) in the ART testbed

Carbó

Molina

2009

Soft Comput

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With the introduction of web services, users require an automated way of determining their reliability and even their matching to personal and subjective preferences. Therefore, trust modelling of web services, managed in an autonomous way by intelligent agents, is a challenging and relevant issue. Due to the dynamic and distributed nature of web services, recommendations of web services from third parties may also play an important role to build and update automated trust models. In this context, the agent reputation and trust (ART) testbed has been used to compare trust models in three international competitions. The testbed runs locally and defines an ART appraisal domain with a simulation engine, although the trust models may be applied to any kind of automated and remote services, such as web services. Our previous works proposed an already-published trust model called AFRAS that used fuzzy sets to represent reputation of service providers and of recommenders of such services. In this paper we describe the extension required in the trust model to participate in these competitions. The extension consists of a trust strategy that applies the AFRAS trust model to the ART testbed concepts and protocols. An implementation of this extension of AFRAS trust model has participated in the (Spanish and International) 2006 ART competitions. Using this ART platform and some of the agents who participated, we executed a set of ART games to evaluate the relevance of trust strategy over trust model, and the advantage of using fuzzy representation of trust and reputation.

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“…There are plenty of these models [2,3] and the mechanisms they use to calculate the trust and reputation values go from simple aggregation of values [4] to the use of probability theory [5], fuzzy logic [6] or the use of entropy [7] just to put some examples. At the end, each model manipulates the input data in a different way trying to obtain the most accurate trust and reputation values for a given subject.…”

mentioning

confidence: 99%

Towards the Next Generation of Computational Trust and Reputation Models

Sabater-Mir

2006

Modeling Decisions for Artificial Intelligence

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The scientific research in the area of computational trust and reputation mechanisms for virtual societies is a recent discipline oriented to increase the reliability and performance of electronic communities by introducing in such communities these well known human social control mechanisms.Computer science has moved from the paradigm of an isolated machine to the paradigm of a network of systems and of distributed computing. Likewise, artificial intelligence is quickly moving from the paradigm of an isolated and non-situated intelligence to the paradigm of a situated, social and collective intelligence. This new "social" dimension is the main responsible of the increasing interest on computational trust and reputation mechanisms applied to electronic societies.Computational trust and reputation systems have been recognized as key factors for successful electronic commerce adoption. These systems are used by intelligent software agents both as a mechanism of search for trustworthy exchange partners and as an incentive in decision-making about whether or not to honour contracts. Reputation is also used in electronic markets as a trust-enforcing, deterrent, and incentive mechanism to avoid cheaters and frauds. Another area of application in agent technology is teamwork and cooperation.However, in spite of the obvious utility of using a trust and reputation system, they are still not a usual element you can find in an agent architecture like it is the case for example of planners or communication modules. Trust and reputation systems still belong to the set of "not so important" elements of an agent architecture. This is something it has to change if we really want artificial socially intelligent entities.If we analyze which computational trust and reputation models are used nowadays, we will notice that only the simplest models are really used (see for example e-Bay[1]). Till now, the use of complex trust and reputation models has been somehow questioned and reduced to academic environments. Why an artificial agent has to use one of these complex models if it is evolving in a simple community with 10 or 15 agents that have limited interaction capabilities? In other words, the applications and environments are too simple to justify a complex trust and reputation model that only has sense in a socially complex environment.However this situation is changing very quickly. The increase of the global connectivity (everything is inter-connected anytime and everywhere) is bringing us a new concept of environment where virtual entities need to interact among

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Trust Management Through Fuzzy Reputation

Cited by 126 publications

References 12 publications

Analysis of the Agent Reputation and Trust Testbed

Analysis of the Agent Reputation and Trust Testbed

An extension of a fuzzy reputation agent trust model (AFRAS) in the ART testbed

Towards the Next Generation of Computational Trust and Reputation Models

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