Dynamics of Argumentation Frameworks

Abstract : This thesis tackles the problem of integrating a new piece of information in an abstract argumenta- tion framework. Such a framework is a directed graph such that its nodes represent the arguments, and the directed edges represent the attacks between arguments. There are different ways to decide which arguments are accepted by the agent who uses such a framework to represent her beliefs. An agent may be confronted with a piece of information such that "this argument should be accepted", which is in contradiction with her current beliefs, represented by her argumentation framework. In this thesis, we have studied several approaches to incorporate a piece of information in an argumenta- tion framework. Our first contribution is an adaptation of the AGM framework for belief revision, which has been de- veloped for characterizing the incorporation of a new piece of information when the agent’s beliefs are represented in a logical setting. We have adapted the rationality postulates from the AGM framework to characterize the revision operators suited to argumentation frameworks, and we have identified several ways to generate the argumentation frameworks resulting from the revision. We have also shown how to use AGM revision as a tool for revising argumentation frameworks. Our approach uses a logical encoding of the argumentation framework to take advantage of the classical re- vision operators, for deriving the expected result. At last, we have studied the problem of enforcing a set of arguments (how to change an argumentation framework so that a given set of arguments becomes an extension). We have developed a new family of operators which guarantee the success of the enforcement process, contrary to the existing approaches, and we have shown that a translation of our approaches into satisfaction and optimization problems makes possible to develop efficient tools for computing the result of the enforcement.
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Jean-Guy Mailly. Dynamics of Argumentation Frameworks. Artificial Intelligence [cs.AI]. Université d'Artois, 2015. English. ⟨tel-02151885⟩

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