Computability and complexity: from a programming perspective
Computability and complexity: from a programming perspective
TRAVOS: Trust and Reputation in the Context of Inaccurate Information Sources
Autonomous Agents and Multi-Agent Systems
Using arguments for making and explaining decisions
Artificial Intelligence
A social-network defence against whitewashing
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Inductively generated trust alignments based on shared interactions
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
An Argumentation-Based Dialog for Social Evaluations Exchange
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Recommender Systems Handbook
Argumentation-based reasoning in agents with varying degrees of trust
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
An abstract framework for reasoning about trust
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Opening the black box of trust
Journal of Logic and Computation
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Agents in open multi-agent systems must deal with the difficult problem of selecting interaction partners in the face of uncertainty about their behaviour. This is especially problematic if they have to interact with an agent they have not interacted with before. In this case they can turn to their peers for information about this potential partner. However, in scenarios where agents may be evaluated according to many different criteria for many different purposes, their peers' evaluations may be mismatched with regards to their own expectations. In this paper we present a novel method, using an argumentation framework, that allows agents to discuss and adapt their trust model. This allows agents to provide, and receive, personalized trust evaluations, better suited to the agent in need, as is shown in a prototypical experiment.