Chop-SAT: A New Approach to Solving SAT and Probabilistic SAT for Agent Knowledge Bases

Thomas C. Henderson, David Sacharny, Amar Mitiche, Xiuyi Fan, Amelia Lessen, Ishaan Rajan, Tessa Nishida

2023

Abstract

An early approach to solve the SAT problem was to convert the disjunctions directly to equations which create an integer programming problem with 0-1 solutions. We have independently developed a similar method which we call Chop-SAT based on geometric considerations. Our position is that Chop-SAT provides a wide range of geometric approaches to find SAT and probabilistic SAT (PSAT) solutions. E.g., one potentially powerful approach to determine that a SAT solution exists is to fit the maximal volume ellipsoid and explore it semi-major axis direction to find an Hn vertex in that direction.

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Paper Citation


in Harvard Style

C. Henderson T., Sacharny D., Mitiche A., Fan X., Lessen A., Rajan I. and Nishida T. (2023). Chop-SAT: A New Approach to Solving SAT and Probabilistic SAT for Agent Knowledge Bases. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 48-54. DOI: 10.5220/0011614400003393


in Bibtex Style

@conference{icaart23,
author={Thomas C. Henderson and David Sacharny and Amar Mitiche and Xiuyi Fan and Amelia Lessen and Ishaan Rajan and Tessa Nishida},
title={Chop-SAT: A New Approach to Solving SAT and Probabilistic SAT for Agent Knowledge Bases},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={48-54},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011614400003393},
isbn={978-989-758-623-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - Chop-SAT: A New Approach to Solving SAT and Probabilistic SAT for Agent Knowledge Bases
SN - 978-989-758-623-1
AU - C. Henderson T.
AU - Sacharny D.
AU - Mitiche A.
AU - Fan X.
AU - Lessen A.
AU - Rajan I.
AU - Nishida T.
PY - 2023
SP - 48
EP - 54
DO - 10.5220/0011614400003393