Rejecting Arguments Based on Doubt in Structured Bipolar Argumentation
Michael A. M\"uller, Srdjan Vesic, Bruno Yun

TL;DR
This paper introduces structured bipolar argumentation frameworks that incorporate doubt-based rejection and sentence-level acceptance, offering a nuanced semantics that better models realistic debate positions.
Contribution
It develops a novel computational approach integrating doubt-based rejection and sentence acceptance, extending existing argumentation semantics with new language and agent position representations.
Findings
Semantics do not force acceptance of all defended arguments.
Provides semantics for acceptable sets of sentences.
Shows deductive support semantics as a special case.
Abstract
This paper develops a new approach to computational argumentation that is informed by philosophical and linguistic views. Namely, it takes into account two ideas that have received little attention in the literature on computational argumentation: First, an agent may rationally reject an argument based on mere doubt, thus not all arguments they could defend must be accepted; and, second, that it is sometimes more natural to think in terms of which individual sentences or claims an agent accepts in a debate, rather than which arguments. In order to incorporate these two ideas into a computational approach, we first define the notion of structured bipolar argumentation frameworks (SBAFs), where arguments consist of sentences and we have both an attack and a support relation between them. Then, we provide semantics for SBAFs with two features: (1) Unlike with completeness-based semantics,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMulti-Agent Systems and Negotiation · Logic, Reasoning, and Knowledge · Embodied and Extended Cognition
