Karen Fullam

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A diverse collection of trust-modeling algorithms for multi-agent systems has been developed in recent years, resulting in significant breadth-wise growth without unified direction or benchmarks. Based on enthusiastic response from the agent trust community, the Agent Reputation and Trust (ART) Testbed initiative has been launched, charged with the task of(More)
Trust is essential when an agent must rely on others to provide resources for accomplishing its goals. When deciding whether to trust, an agent may rely on, among other types of trust information, its past experience with the trustee or on reputations provided by third-party agents. However, each type of trust information has strengths and weaknesses: trust(More)
The Agent Reputation and Trust (ART) Testbed initiative has been launched with the goal of establishing a testbed for agent reputationand trustrelated 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,(More)
An agent's <i>trust decision strategy</i> consists of the agent's policies for making trust-related decisions, such as who to trust, how trustworthy to be, what reputations to believe, and when to tell truthful reputations. In reputation exchange networks, learning trust decision strategies is complex, compared to non-reputation-communicating systems. When(More)
The Agent Reputation and Trust (ART) Testbed [1] provides functionality for researchers of trust and reputation in multi-agent systems. As a versatile, universal experimentation site, the ART Testbed scopes relevant trust research problems and unites researchers toward solutions via unified experimentation methods. Through objective, well-defined metrics,(More)
1Laboratory for Intelligent Processes and Systems, University of Texas at Austin, USA 2Center for Mathematics and Computer Science (CWI), Amsterdam, The Netherlands 3École Nationale Supérieure des Mines, Saint-Étienne, France 4Institute of Cognitive Science and Technology (ISTC), National Research Council (CNR), Rome, Italy 5IT Transfer Office, Darmstadt(More)
Mechanisms for modeling trust and reputation to improve robustness and performance in multi-agent societies make up a growing field of research that has yet to establish unified direction or benchmarks. The trust research community will benefit significantly from the development of a competition testbed; such development is currently in progress under the(More)