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Part of the book series: Lecture Notes in Computer Science ((TCCI,volume 7270))

Abstract

The process of reaching an agreement about the meaning of a set of terms is known as Meaning Negotiation. The problem of representing this process contains some sub-problems: to represent the knowledge of the agents about the meaning of the negotiating set of terms, to model the behaviour of the agents involved and to define the agreement and disagreement conditions.

Although a large attention from many diverse communities has been driven to this theme in the recent literature of Artificial Intelligence and Knowledge Representation, the results of these investigations depend upon the number of the involved agents. The mechanism of reaching an agreement has been largely studied in the Game Theory community, but only for quantitative objects to be negotiated.

In this paper we approach the problem of defining a general framework that can be used to formalise the steps that brings two agents in one case or a group of more than two agents in the other one to reach an agreement about the meaning of a set of terms. In particular, once we have defined a logical framework to represent the situation of two agents that negotiate we define an algorithm automating the Meaning Negotiation process and study its computational properties. We then extend the algorithm to a framework in which negotiating agents are more than two.

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Burato, E., Cristani, M. (2012). The Process of Reaching Agreement in Meaning Negotiation. In: Nguyen, N.T. (eds) Transactions on Computational Collective Intelligence VII. Lecture Notes in Computer Science, vol 7270. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32066-8_1

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  • DOI: https://doi.org/10.1007/978-3-642-32066-8_1

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