The Agent Reputation and Trust (ART) Testbed Architecture

  • Authors:
  • Karen K. Fullam;Tomas B. Klos;Guillaume Muller;Jordi Sabater-Mir;Zvi Topol;K. Suzanne Barber;Jeffrey Rosenschein;Laurent Vercouter

  • Affiliations:
  • Laboratory for Intelligent Processes and Systems, University of Texas at Austin, USA;Center for Mathematics and Computer Science (CWI), Amsterdam, The Netherlands;École Nationale Supérieure des Mines, Saint-Étienne, France;Institute of Cognitive Science and Technology, CNR, Rome, Italy;MAS Research Group---Critical MAS, Hebrew University, Jerusalem, Israel;Laboratory for Intelligent Processes and Systems, University of Texas at Austin, USA;MAS Research Group---Critical MAS, Hebrew University, Jerusalem, Israel;École Nationale Supérieure des Mines, Saint-Étienne, France

  • Venue:
  • Proceedings of the 2005 conference on Artificial Intelligence Research and Development
  • Year:
  • 2005

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Abstract

The Agent Reputation and Trust (ART) Testbed initiative has been launched with the goal of establishing a testbed for agent reputation-and trust-related technologies. This testbed serves in two roles: (1) as a competition forum in which researchers can compare their technologies against objective metrics, and (2) as a suite of tools with flexible parameters, allowing researchers to perform customizable, easily-repeatable experiments. In the testbed's art appraisal domain, agents, who valuate paintings for clients, may gather opinions from other agents to produce accurate appraisals. This paper first gives a brief overview of the testbed domain problem to orient the reader to the game rules. A discussion of the ART Testbed implementation architecture is presented, explaining the functionality of the testbed's Game Server, Simulation Engine, Database, User Interfaces, and Agent Skeleton.