Abstract
Constraint Satisfaction Problems (CSPs) are the formalization of a large range of problems that emerge from computer science. The solving methodology described here is based on Naming Games (NGs). NGs were introduced to represent N agents that have to bootstrap an agreement on a name to give to an object (i.e., a word). In this paper we focus on solving both Fuzzy NGs and Fuzzy Distributed CSPs (Fuzzy DCSPs) with an algorithm inspired by NGs. In this framework, each proposed solution is associated with a preference represented as a fuzzy score. We want the agents to find the solution, which is associated with the highest preference value among all solutions. The two main features that distinguish this methodology from classical Fuzzy DCSPs algorithms are that i) the system can react to small instance changes, and ii) the fact the algorithm does not require a pre-agreed agent/variable ordering.
This work was carried out during the tenure of the ERCIM “Alain Bensoussan” Fellowship Programme, which is supported by the Marie Curie Co-funding of Regional, National and International Programmes (COFUND) of the European Commission.
Research partially supported by MIUR PRIN 2010-2011 2010FP79LR project: “Logical Methods of Information Management”.
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Bistarelli, S., Gosti, G., Santini, F. (2013). Solving Fuzzy Distributed CSPs: An Approach with Naming Games. In: Baldoni, M., Dennis, L., Mascardi, V., Vasconcelos, W. (eds) Declarative Agent Languages and Technologies X. DALT 2012. Lecture Notes in Computer Science(), vol 7784. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37890-4_7
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