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.
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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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