Online Handbook of Argumentation for AI: Volume 4
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Abstract (arXiv)
This volume contains revised versions of the papers selected for the fourth volume of the Online Handbook of Argumentation for AI (OHAAI). Previously, formal theories of argument and argument interaction have been proposed and studied, and this has led to the more recent study of computational models of argument. Argumentation, as a field within artificial intelligence (AI), is highly relevant for researchers interested in symbolic representations of knowledge and defeasible reasoning. The purpose of this handbook is to provide an open access and curated anthology for the argumentation research community. OHAAI is designed to serve as a research hub to keep track of the latest and upcoming PhD-driven research on the theory and application of argumentation in all areas related to AI.
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References · 13
- 2017Explanation in Artificial Intelligence: Insights from the Social Sciencescited by 1,201
- 2016Cooperative Inverse Reinforcement Learningcited by 298
- 2013Causal Inference and Causal Explanation with Background Knowledgecited by 168
- 2013Learning Equivalence Classes of Bayesian Networks Structurescited by 75
- 2021Argumentative XAI: A Surveycited by 66
- 2020CASTLE: Regularization via Auxiliary Causal Graph Discoverycited by 41
- 2020Combining Experts' Causal Judgmentscited by 6
- 2022Causal Discovery and Knowledge Injection for Contestable Neural Networks (with Appendices)cited by 6
- 2021Weakly Complete Semantics Based on Undecidedness Blockingcited by 3
- 2020Stability in Abstract Argumentationcited by 2
- 2020Online Handbook of Argumentation for AI: Volume 1cited by 1
- 2022Revisiting initial sets in abstract argumentationcited by 1
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- 2022Online Handbook of Argumentation for AI: Volume 3cited by 1
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