A Logical Theory about Dynamics in Abstract Argumentation

Richard Booth (1, 2) , Souhila Kaci (3) , Tjitze Rienstra (4) , Leendert van Der Torre (4)

1 SnT - Interdisciplinary Centre for Security, Reliability and Trust [Luxembourg]
2 FSTC - Faculty of Science, Technology and Communication [Luxembourg]
3 GRAPHIK - Graphs for Inferences on Knowledge
4 ICR - Individual and Collective Reasoning

We address dynamics in abstract argumentation using a logical theory where an agent's belief state consists of an argumentation framework (AF, for short) and a constraint that encodes the outcome the agent believes the AF \emph{should} have. Dynamics enters in two ways: (1) the constraint is strengthened upon learning that the AF should have a certain outcome and (2) the AF is expanded upon learning about new arguments/attacks. A problem faced in this setting is that a constraint may be inconsistent with the AF's outcome. We discuss two ways to address this problem: First, it is still possible to form consistent \emph{fallback beliefs}, i.e., beliefs that are most plausible given the agent's AF and constraint. Second, we show that it is always possible to find AF expansions to restore consistency. Our work combines various individual approaches in the literature on argumentation dynamics in a general setting.

Domaines: Intelligence artificielle [cs.AI]

Richard Booth, Souhila Kaci, Tjitze Rienstra, Leendert van Der Torre. A Logical Theory about Dynamics in Abstract Argumentation. SUM: Scalable Uncertainty Management, Sep 2013, Washington, DC, United States. pp.148-161, ⟨10.1007/978-3-642-40381-1_12⟩. ⟨lirmm-00863487⟩