Intrinsic Argument Strength in Structured Argumentation: a Principled Approach
This work addresses a foundational issue in AI reasoning for researchers in argumentation theory, but it is incremental as it builds on existing structured argumentation frameworks.
The paper tackles the problem of assigning intrinsic strength to arguments in structured argumentation by proposing methods based on the strengths of premises and inference rules, resulting in a generalized system for creating such methods and analyzing their properties against defined principles.
Abstract argumentation provides us with methods such as gradual and Dung semantics with which to evaluate arguments after potential attacks by other arguments. Some of these methods can take intrinsic strengths of arguments as input, with which to modulate the effects of attacks between arguments. Coming from abstract argumentation, these methods look only at the relations between arguments and not at the structure of the arguments themselves. In structured argumentation the way an argument is constructed, by chaining inference rules starting from premises, is taken into consideration. In this paper we study methods for assigning an argument its intrinsic strength, based on the strengths of the premises and inference rules used to form said argument. We first define a set of principles, which are properties that strength assigning methods might satisfy. We then propose two such methods and analyse which principles they satisfy. Finally, we present a generalised system for creating novel strength assigning methods and speak to the properties of this system regarding the proposed principles.