Evolutionary-inspired approach to compare trust models in agent simulations

e-Archivo Repository

Show simple item record

dc.contributor.author Carbó Rubiera, Javier Ignacio
dc.contributor.author Molina López, José Manuel
dc.date.accessioned 2018-03-23T13:37:45Z
dc.date.available 2018-03-23T13:37:45Z
dc.date.issued 2015
dc.identifier.bibliographicCitation AI Communications (2015), 28(3) 429-440.
dc.identifier.issn 0921-7126
dc.identifier.uri http://hdl.handle.net/10016/26564
dc.description.abstract In many dynamic open systems, agents have to interact with one another to achieve their goals. These interactions pose challenges in relation to the trust modeling of agents which aim to facilitate an agent's decision making regarding the uncertainty of the behaviour of its peers. A lot of literature has focused on describing trust models, but less on evaluating and comparing them. The most extensive way to evaluate trust models is executing simulations with different conditions and a given combination of different types of agents (honest, altruist, etc.). Trust models are then compared according to efficiency, speed of convergence, adaptability to sudden changes, etc. Our opinion is that such evaluation measures do not represent a complete way to determine the best trust model, since they do not include testing which one is evolutionarily stable. Our contribution is the definition of a new way to compare trust models observing their ability to become dominant. It consists of finding out the right equilibrium of trust models in a multiagent system that is evolutionarily stable, and then observing which agent became dominant. We propose a sequence of simulations where evolution is implemented assuming that the worst agent in a simulation would replace its trust model with the best one in such simulation. Therefore the ability to become dominant could be an interesting feature for any trust model. Testing this ability through this evolutionary-inspired approach is then useful to compare and evaluate trust models in agent systems. Specifically we have applied our evaluation method to the Agent Reputation and Trust competitions held at 2006, 2007 and 2008 AAMAS conferences. We observe then that the resulting ranking of comparing the agents ability of becoming dominant is different from the official one where the winner was decided running a game with a representative of all participants several times.
dc.description.sponsorship This work was supported in part by projects MINECO TEC2012-37832-C02-01, CICYT TEC2011-28626-C02-02, CAM CONTEXTS (S2009/TIC-1485)
dc.format.extent 11
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher IOS Press
dc.rights ©2015 IOS Press
dc.subject.other Trust models
dc.subject.other Autonomous agents
dc.subject.other Evolutionary game theory
dc.title Evolutionary-inspired approach to compare trust models in agent simulations
dc.type article
dc.subject.eciencia Informática
dc.identifier.doi https://doi.org/10.3233/AIC-140654
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. TEC2012-37832-C02-01
dc.relation.projectID Gobierno de España. TEC-2010-21619-C01-01
dc.relation.projectID Comunidad de Madrid. S2009/ESP-1691/MODELICO
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 429
dc.identifier.publicationissue 3
dc.identifier.publicationlastpage 440
dc.identifier.publicationtitle AI Communications
dc.identifier.publicationvolume 28
dc.identifier.uxxi AR/0000017152
 Find Full text

Files in this item

*Click on file's image for preview. (Embargoed files's preview is not supported)

This item appears in the following Collection(s)

Show simple item record