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Cooperation and Competition in ALIAS: A Logic Framework for Agents that Negotiate

Anna Ciampolini, Evelina Lamma, Paola Mello, Francesca Toni, Paulo Torroni

Journal Article
Annals of Mathematics and Artificial Intelligence
Volume 37
Issues 1–2
Springer Science+Business Media B.V.
ISSN 1012-2443
DOI 10.1023/A:1020259411066

This paper presents ALIAS, an agent architecture based on intelligent logic agents, where the main form of agent reasoning is abduction. The system is particularly suited for solving problems where knowledge is incomplete, where agents may need to make reasonable hypotheses about the problem domain and other agents. ALIAS agents are pro-active, exhibiting a goal-directed behavior, and autonomous, since each one can solve problems using its own private knowledge base. ALIAS agents are also social, because they are able to interact with other agents, in order to cooperatively solve problems. The coordination mechanisms are modeled by means of LAILA, a logic-based language which allows to express intra-agent reasoning and inter-agent coordination. We show how LAILA can be used to implement inter-agent dialogues, e.g., for negotiation. In particular, LAILA is well-suited to coordinate the process of negotiation aimed at exchanging resources between agents, thus allowing them to execute the plans to achieve their goal.

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