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An answer set programming-based implementation of epistemic probabilistic event calculus

D'Asaro, Fabio Aurelio; Bikakis, Antonis; Dickens, Luke; Miller, Rob; (2024) An answer set programming-based implementation of epistemic probabilistic event calculus. International Journal of Approximate Reasoning , 165 , Article 109101. 10.1016/j.ijar.2023.109101. Green open access

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Abstract

We describe a general procedure for translating Epistemic Probabilistic Event Calculus (EPEC) action language domains into Answer Set Programs (ASP), and show how the Python-driven features of the ASP solver Clingo can be used to provide efficient computation in this probabilistic setting. EPEC supports probabilistic, epistemic reasoning in domains containing narratives that include both an agent's own action executions and environmentally triggered events. Some of the agent's actions may be belief-conditioned, and some may be imperfect sensing actions that alter the strengths of previously held beliefs. We show that our ASP implementation can be used to provide query answers that fully correspond to EPEC's own declarative, Bayesian-inspired semantics.

Type: Article
Title: An answer set programming-based implementation of epistemic probabilistic event calculus
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.ijar.2023.109101
Publisher version: http://dx.doi.org/10.1016/j.ijar.2023.109101
Language: English
Additional information: Copyright © 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Answer set programming (ASP); Epistemic reasoning; Probabilistic reasoning; Event calculus; Knowledge representation; Artificial intelligence
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of Arts and Humanities
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of Arts and Humanities > Dept of Information Studies
URI: https://discovery.ucl.ac.uk/id/eprint/10185292
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