A Syntactical Approach to Qualitative Constraint Networks Merging

Jean-Francois Condotta (1) , Souhila Kaci (1) , Pierre Marquis (1) , Nicolas Schwind (1)

1 CRIL - Centre de Recherche en Informatique de Lens

We address the problem of merging qualitative constraint networks (QCNs) representing agents local preferences or beliefs on the relative position of spatial or temporal entities. Two classes of merging operators which, given a set of input QCNs defined on the same qualitative formalism, return a set of qualitative configurations representing a global view of these QCNs, are pointed out. These operators are based on local distances and aggregation functions. In contrast to QCN merging operators recently proposed in the literature, they take account for each constraint from the input QCNs within the merging process. Doing so, inconsistent QCNs do not need to be discarded at start, hence agents reporting locally consistent, yet globally inconsistent pieces of information (due to limited rationality) can be taken into consideration.

Domaines: Intelligence artificielle [cs.AI]

Jean-Francois Condotta, Souhila Kaci, Pierre Marquis, Nicolas Schwind. A Syntactical Approach to Qualitative Constraint Networks Merging. LPAR: Logic for Programming, Artificial Intelligence and Reasoning, Oct 2010, Yogyakarta, Indonesia. pp.233-247, ⟨10.1007/978-3-642-16242-8_17⟩. ⟨hal-00866877⟩