A Probabilistic Theory of Abductive Reasoning

Nicolas Espinosa Dice, Megan Kaye, Hana Ahmed, Hana Ahmed, George Montañez

Abstract

We present an abductive search strategy that integrates creative abduction and probabilistic reasoning to produce plausible explanations for unexplained observations. Using a graphical model representation of abductive search, we introduce a heuristic approach to hypothesis generation, comparison, and selection. To identify creative and plausible explanations, we propose 1) applying novel structural similarity metrics to a search for simple explanations, and 2) optimizing for the probability of a hypothesis’ occurrence given known observations.

Download


Paper Citation


in Harvard Style

Espinosa Dice N., Kaye M., Ahmed H. and Montañez G. (2021). A Probabilistic Theory of Abductive Reasoning.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-484-8, pages 562-571. DOI: 10.5220/0010195405620571


in Bibtex Style

@conference{icaart21,
author={Nicolas Espinosa Dice and Megan Kaye and Hana Ahmed and George Montañez},
title={A Probabilistic Theory of Abductive Reasoning},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2021},
pages={562-571},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010195405620571},
isbn={978-989-758-484-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - A Probabilistic Theory of Abductive Reasoning
SN - 978-989-758-484-8
AU - Espinosa Dice N.
AU - Kaye M.
AU - Ahmed H.
AU - Montañez G.
PY - 2021
SP - 562
EP - 571
DO - 10.5220/0010195405620571