Games That Agents Play: A Formal Framework for Dialogues between Autonomous Agents
Journal of Logic, Language and Information
A Taxonomy of Recommender Agents on theInternet
Artificial Intelligence Review
Proceedings of the 10th international conference on Intelligent user interfaces
Securing Agent-Oriented Systems: An Argumentation and Reputation-based Approach
ITNG '07 Proceedings of the International Conference on Information Technology
A model of a trust-based recommendation system on a social network
Autonomous Agents and Multi-Agent Systems
A Dialogue-Game Approach for Norm-Based MAS Coordination
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
How Argumentation can Enhance Dialogues in Social Networks
Proceedings of the 2010 conference on Computational Models of Argument: Proceedings of COMMA 2010
Research opportunities for argumentation in social networks
Artificial Intelligence Review
Arguing about social evaluations: From theory to experimentation
International Journal of Approximate Reasoning
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Recommendation in social networks is a new area of research that is still in its early beginnings. In this framework, every user can act as an individual recommender for its neighbours in the network. However, social networks are highly dynamic environments where the structure of the network and the information spread across it evolve quickly over time. In these settings, a suitable recommender must be able to manage continuous changes and to provide users with up-to-date and customised recommendations. With this aim, the theory of dialogue games has been applied to manage recommendation dialogues in social networks in this research. As a result, a dialogue game for controlling the interaction between an agent asking for recommendations to other personal agents that are its neighbours in the network has been designed. In addition, a complex decision-making policy based on this game has been developed and tested in a simulation scenario. The results are shown and discussed in this paper.