Argumentation in Flux – Modelling change in the theory of argumentation
Members of the defense committee:
Chairman : Prof. Dr. Lluis Godo, Institut d’Investigacio en Intelligencia Artificial, Bellaterra, Spain
Vice-chairman : Prof. Dr. Pietro Baroni, Universita degli Studi di Brescia, Italy
Co-Supervisor : Prof. Dr. Leon van der Torre, Université du Luxembourg
Co-Supervisor: Prof. Dr. Souhila Kaci, Université de Montpellier, France
Member: Prof. Dr. Beishui Liao, Zhejiang University, China
Member: Dr. Richard Booth, Université du Luxembourg
Abstract
Dung’s theory of abstract argumentation is a widely used formalism in the field of artificial intelligence. It is used to model various types of reasoning, by representing conflicting or defeasible information using an argumentation framework, i.e., a set of arguments and an attack relation. Different so called semantics have been proposed in the literature to determine, given an argumentation framework, the justifiable points of view on the acceptability of the arguments. The research in this thesis is motivated by the idea that argumentation is not a static process, and that a better understanding of the fundamentals and applications of the theory of abstract argumentation requires a dynamic perspective. We address this issue from three points of view.
First, we identify and investigate two types of change in argumentation. We call them intervention and observation, due to their similarity to the similarly named types of change in the theory of causal Bayesian networks. While intervention amounts to change due to actions (i.e., bringing new arguments/attacks into play), observation amounts to revision due to new information from the environment. We model these two types of change as two types of inference relations. This allows us to contrast and characterize the behaviour of the two types of change, under a number of different semantics, in terms of properties satisfied by the respective inference relations.
Second, we investigate the relation between abduction in logic programming and change in argumentation. We show that, on the abstract level, changes to an argumentation framework may act as hypotheses to explain an observation. The relation with abduction in logic programming lies in the fact that this abstract model can be instantiated on the basis of an abductive logic program, just like an abstract argumentation framework can be instantiated on the basis of a logic program. We furthermore present dialogical proof theories for the main reasoning problem, i.e., finding hypotheses that explain an observation.
Third, we look at change in preference-based argumentation. Preferences have been introduced in argumentation to encode, for example, relative strength of arguments. An underexposed aspect in these models is change of preferences. We present a dynamic model of preferences in argumentation, based on what we call property-based argumentation frameworks. It is based on Dietrich and List’s model of property-based preference and provides an account of how and why preferences in argumentation may change. The idea is that preferences over arguments are derived from preferences over properties of arguments and change as the result of moving to different motivational states. We also provide a dialogical proof theory that establishes whether there exists some motivational state in which an argument is accepted.
