Encoding Belief Revision Operators in Abstract Dialectical Frameworks

Master's thesis by Umer Mushtaq

Supervisor Sebastian Rudolph, Sarah Alice Gaggl
Computational Logic
11 Februar 2016 – 7 Oktober 2016

An important area of study in Knowledge Representation is to investigate how an agent deals with contradictory truth assertions by different entities and emerges with a coherent epistemic outcome in light of these contradictions. Belief Revision and Abstract Argumentation are two areas of research, among others, that deal with this problem. In Belief Revision, an agent is concerned with what truth assertion(s) to exclude from it’s original belief state in light of a newly encountered truth assertion(s) which conflicts with it’s existing belief set. Researchers have suggested many belief revision operators, categorized as formula-based and model-based operators, in literature each with a unique approach to solving the inconsistency in the knowl- edge of an agent. Abstract Argumentation is a mechanism to arrive at a coherent result in a scenario with multiple conflicting truth assertions. Abstract Dialectical Frameworks (ADFs) are a special class of argumentation frameworks where the acceptance of a truth assertion can be made dependent upon the satisfaction of an associated condition. ADFs are more powerful in that they are able to encode more complex relations between arguments. Semantics of ADFs specify what coherent outcomes can be reached given conflicting truth assertions. In this work, we seek to establish correspondence between various belief revision operators and syntactic and semantic dynamics of ADFs. We will seek to define equivalent ADFs that simulate belief revision operators.