A Framework for Combining Defeasible Argumentation with Labeled Deduction
Carlos Iván Chesñevar, Guillermo Ricardo Simari
Abstract
In the last years, there has been an increasing demand of a variety of logical systems, prompted mostly by applications of logic in AI and other related areas. Labeled Deductive Systems (LDS) were developed as a flexible methodology to formalize such a kind of complex logical systems. Defeasible argumentation has proven to be a successful approach to formalizing commonsense reasoning, encompassing many other alternative formalisms for defeasible reasoning. Argument-based frameworks share some common notions (such as the concept of argument, defeater, etc.) along with a number of particular features which make it difficult to compare them with each other from a logical viewpoint. This paper introduces LDSar, a LDS for defeasible argumentation in which many important issues concerning defeasible argumentation are captured within a unified logical framework. We also discuss some logical properties and extensions that emerge from the proposed framework.
Create a lesson
Related papers
Can Language Models Play the Wikipedia Game?
Alexander Hickey, Joanna Knight, James Bishop
RATED: Reliability-Aware AI Agent Tool Retrieval via Execution Dynamics
Weiliang Chen, Song Liao
X-AgentRed: Red-Teaming Personal Agents in Evolving Multi-Service Ecosystems
Yeonsung Jung, Zhiyuan Wang, Zifan Wang et al.
Studying Comics at Scale with Artificial Intelligence: The PAGE Framework and Three Studies of American Comics and Japanese Manga
Emilio Ferrara
UkrMeme: Multimodal Explainable Persuasion Detection in Ukrainian Memes
Nazar Andrushko, Vera Schmitt, Veronika Solopova
A Privileged Teacher That Only Scores Cannot Search: Critique-Conditioned On-Policy Self-Distillation for Reasoning
Mayug Maniparambil, Ayush Rai, Ekansh Verma et al.