Argument evaluation in multi-agent justification logics

Abstract

Argument evaluation , one of the central problems in argumentation theory, consists in studying what makes an argument a good one. This paper proposes a formal approach to argument evaluation from the perspective of justification logic. We adopt a multi-agent setting, accepting the intuitive idea that arguments are always evaluated by someone. Two general restrictions are imposed on our analysis: non-deductive arguments are left out and the goal of argument evaluation is fixed: supporting a given proposition. Methodologically, our approach uses several existing tools borrowed from justification logic, awareness logic, doxastic logic and logics for belief dependence. We start by introducing a basic logic for argument evaluation, where a list of argumentative and doxastic notions can be expressed. Later on, we discuss how to capture the mentioned form of argument evaluation by defining a preference operator in the object language. The intuitive picture behind this definition is that, when assessing a couple of arguments, the agent puts them to a test consisting of several criteria (filters). As a result of this process, a preference relation among the evaluated arguments is established by the agent. After showing that this operator suffers a special form of logical omniscience, called preferential omniscience, we discuss how to define an explicit version of it, more suitable to deal with non-ideal agents. The present work exploits the formal notion of awareness in order to model several informal phenomena: awareness of sentences, availability of arguments and communication between agents and external sources (advisers). We discuss several extensions of the basic logic and offer completeness and decidability results for all of them.

Qualitative uncertainty and dynamics of argumentation through dynamic logic

“…In recent years, a few papers dealing with the combination of epistemic logic and formal argumentation have appeared. Broadly speaking, these works can be divided into two main branches: (i) those trying to provide a formalisation of the notion of justified belief based on argumentative tools such as [44,62,63,61,21,22]; and (ii) those using epistemic models for reasoning about uncertain AFs such as [60,59,49,50]. Clearly, the second one is strongly connected-both conceptually and technically-to some of the ideas presented here.…”

An Abstract Look at Awareness Models and Their Dynamics

“…This enables us to express higher-order uncertainty about awareness of arguments [35], which is in turn crucial for modelling strategic reasoning in an argumentative environment [36] and its dynamics [32,33]. In a similar vein, O-models have been applied to more structured frameworks for argumentation [13,14], with O understood as a set of ASPIC + arguments [30].…”

A Hybrid Approach to Representing Shared Conceptualization in Decentralized AI Systems: Integrating Epistemology, Ontology, and Epistemic Logic

“…It is used to formally specify and represent shared conceptualization in AI systems. This is particularly important in decentralized environments, where the sharing of knowledge is crucial for the effective functioning of the system [21,22].…”