2022 IJCAI IJCAI 2022

Abstract Argumentation Frameworks with Marginal Probabilities

Abstract

In the context of probabilistic AAFs, we intro- duce AAFs with marginal probabilities (mAAFs) requiring only marginal probabilities of argu- ments/attacks to be specified and not relying on the independence assumption. Reasoning over mAAFs requires taking into account multiple probability distributions over the possible worlds, so that the probability of extensions is not determined by a unique value, but by an interval. We focus on the problems of computing the max and min probabil- ities of extensions over mAAFs under Dung’s se- mantics, characterize their complexity, and provide closed formulas for polynomial cases.

🌉 Interdisciplinary Bridge — Knowledge & Reasoning and Machine Learning and Mathematics & Optimization
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning