teacyetal - The ART of IAM: The Winning Strategy for the...

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Unformatted text preview: The ART of IAM: The Winning Strategy for the 2006 Competition [ART TESTBED SPECIAL SESSION] W. T. Luke Teacy, Trung Dong Huynh, Rajdeep K. Dash, Nicholas R. Jennings and Jigar Patel School of Electronics and Computer Science University of Southampton Southampton, SO17 1BJ, United Kingdom { wtlt,tdh,rkd,nrj } @ecs.soton.ac.uk jpatel@mckinsey.com Michael Luck Department of Computer Science Kings College London, WC2R 2LS United Kingdom michael.luck@kcl.ac.uk ABSTRACT In many dynamic open systems, agents have to interact with one another to achieve their goals. Here, agents may be self-interested, and when trusted to perform an action for others, may betray that trust by not performing the actions as required. In addition, due to the size of such systems, agents will often interact with other agents with which they have little or no past experience. This situation has led to the development of a number of trust and reputation mod- els, which aim to facilitate an agents decision making in the face of uncertainty regarding the behaviour of its peers. However, these multifarious models employ a variety of dif- ferent representations of trust between agents, and measure performance in many different ways. This has made it hard to adequately evaluate the relative properties of different models, raising the need for a common platform on which to compare competing mechanisms. To this end, the ART Testbed Competition has been proposed, in which agents using different trust models compete against each other to provide services in an open marketplace. In this paper, we present the winning strategy for this competition in 2006, provide an analysis of the factors that led to this success, and discuss lessons learnt from the competition about issues of trust in multiagent systems in general. Our strategy, IAM, is Intelligent (using statistical models for opponent modelling), Abstemious (spending its money parsimoniously based on its trust model) and Moral (providing fair and honest feedback to those that request it). 1. INTRODUCTION Trust constitutes an important facet of multiagent systems research since it provides a form of distributed social con- trol within highly dynamic and open systems whereby agents form opinions about other agents based on their past interac- tions, as well as from reports of other agents [8]. As a result, a number of trust models and strategies have been proposed in order to deal with distinct aspects of the interactions be- tween agents (e.g. to deal with lying agents [1], to model and learn the behaviour of other agents [10, 9] and to fuse information from disparate sources and models [5]). This, in turn, has rendered it hard to compare trust strategies since the underlying problem addressed by these strategies has been different. Therefore, in order to provide a common platform on which researchers can compare their technolo- gies against objective metrics the Agent Reputation and Trust (ART) Testbed Competition has been proposed [3].Trust (ART) Testbed Competition has been proposed [3]....
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This note was uploaded on 08/25/2011 for the course EGN 3060c taught by Professor Sukthankar,g during the Fall '08 term at University of Central Florida.

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teacyetal - The ART of IAM: The Winning Strategy for the...

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