Preferential Structures for Comparative Probabilistic Reasoning

Authors

  • Matthew Harrison-Trainor University of California, Berkeley
  • Wesley Holliday University of California, Berkeley
  • Thomas Icard, III Stanford University

DOI:

https://doi.org/10.1609/aaai.v31i1.10695

Keywords:

comparative probability, qualitative probability, imprecise probability, preferential structures, logic, complexity

Abstract

Qualitative and quantitative approaches to reasoning about uncertainty can lead to different logical systems for formalizing such reasoning, even when the language for expressing uncertainty is the same. In the case of reasoning about relative likelihood, with statements of the form φ 

AAAI-2017 Proceedings Cover

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Published

2017-02-12

How to Cite

Harrison-Trainor, M., Holliday, W., & Icard, III, T. (2017). Preferential Structures for Comparative Probabilistic Reasoning. Proceedings of the AAAI Conference on Artificial Intelligence, 31(1). https://doi.org/10.1609/aaai.v31i1.10695

Issue

Vol. 31 No. 1 (2017): Thirty-First AAAI Conference on Artificial Intelligence

Section

AAAI Technical Track: Knowledge Representation and Reasoning