Ensuring reference independence and cautious monotony in abstract argumentation

in International Journal of Approximate Reasoning (2022), 140

In the symbolic artificial intelligence community, abstract argumentation with its semantics, i.e. approaches for defining sets of valid conclusions (extensions) that can be derived from argumentation ... [more ▼]

In the symbolic artificial intelligence community, abstract argumentation with its semantics, i.e. approaches for defining sets of valid conclusions (extensions) that can be derived from argumentation graphs, is considered a promising method for non-monotonic reasoning. However, from a sequential perspective, abstract argumentation-based decision-making processes typically do not guarantee an alignment with common formal notions to assess consistency; in particular, abstract argumentation can, in itself, not enforce the satisfaction of relational principles such as reference independence (based on a key principle of microeconomic theory) and cautious monotony. In this paper, we address this issue by introducing different approaches to ensuring reference independence and cautious monotony in sequential argumentation: a reductionist, an expansionist, and an extension-selecting approach. The first two approaches are generically applicable, but may require comprehensive changes to the corresponding argumentation framework. In contrast, the latter approach guarantees that an extension of the corresponding argumentation framework can be selected to satisfy the relational principle by requiring that the used argumentation semantics is weakly reference independent or weakly cautiously monotonous, respectively, and also satisfies some additional straightforward principles. To highlight the relevance of the approach, we illustrate how the extension-selecting approach to reference independent argumentation can be applied to model (boundedly) rational economic decision-making. [less ▲]

Explainable Reasoning in Face of Contradictions: From Humans to Machines

in Calvaresi, Davide; Najjar, Amro; Winikoff, Michael (Eds.) et al Explainable and Transparent AI and Multi-Agent Systems - Third International Workshop, EXTRAAMAS 2021, Virtual Event, May 3-7, 2021, Revised Selected Papers (2021)

A well-studied trait of human reasoning and decision-making is the ability to not only make decisions in the presence of contradictions, but also to explain why a decision was made, in particular if a ... [more ▼]

A well-studied trait of human reasoning and decision-making is the ability to not only make decisions in the presence of contradictions, but also to explain why a decision was made, in particular if a decision deviates from what is expected by an inquirer who requests the explanation. In this paper, we examine this phenomenon, which has been extensively explored by behavioral economics research, from the perspective of symbolic artificial intelligence. In particular, we introduce four levels of intelligent reasoning in face of contradictions, which we motivate from a microeconomics and behavioral economics perspective. We relate these principles to symbolic reasoning approaches, using abstract argumentation as an exemplary method. This allows us to ground the four levels in a body of related previous and ongoing research, which we use as a point of departure for outlining future research directions. [less ▲]

A Brief Introduction to the Shkop Approach to Conflict Resolution in Formal Argumentation

in Liao, Beishui; Jieting, Luo; van der Torre, Leon (Eds.) Logics for New-Generation AI 2021 (2021)

In this paper, we formalise the Shkop approach to conflict resolution in formal argumentation, in which we start with an empty abstract argumentation framework AF and an initially empty set of inferred ... [more ▼]

In this paper, we formalise the Shkop approach to conflict resolution in formal argumentation, in which we start with an empty abstract argumentation framework AF and an initially empty set of inferred arguments. Then, we expand AF one argument at a time, and evaluate after each expansion if i) arguments that have previously been inferred can be kept (or have to be discarded due to sufficient doubt) and ii) if the newly added argument can be added to the set of inferred arguments. Based on this idea, we introduce a novel approach for designing abstract argumentation semantics. As a particular semantics, we define grounded Shkop semantics – a naive set-based argumentation semantics that does not inhibit a well-known problem of CF2 semantics. [less ▲]