Proceedings of the Seventh International Workshop on Preferences and Soft Constraints

Some interactions among agents can be well modeled with argumentation theory. We suggest soft constraints as a mean to parametrically represent and solve “weighted” and bipolar argumentation problems: different kinds of (bipolar) preference levels related to arguments, e.g. a score representing a “fuzziness”, a “cost” or a probability level of each argument, can be represented by choosing different semiring algebraic structures. The novel idea is to provide a common computational and quantitative framework where the computation of the classical Dung’s semantics has an associated score representing “how much good” the computed set is. Moreover, we propose a mapping from weighted and bipolar Argumentation Frameworks to Soft Constraint Satisfaction Problems (SCSPs); with this mapping we can compute Dung semantics (e.g. admissible and stable) by solving the related SCSP. To implement this mapping we use JaCoP, a Java constraint solver.

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