Abstract

Solving a decision theory problem usually involves finding the actions, among a set of possible ones, which optimize the expected reward, while possibly accounting for the uncertainty of the environment. In this paper, we introduce the possibility to encode decision theory problems with Probabilistic Answer Set Programming under the credal semantics via decision atoms and utility attributes. To solve the task, we propose an algorithm based on three layers of Algebraic Model Counting, that we test on several synthetic datasets against an algorithm that adopts answer set enumeration. Empirical results show that our algorithm can manage non-trivial instances of programs in a reasonable amount of time.

Details

Title
Solving Decision Theory Problems with Probabilistic Answer Set Programming
Author
Azzolini, Damiano 1   VIAFID ORCID Logo  ; BELLODI, ELENA 2   VIAFID ORCID Logo  ; Kiesel, Rafael 3 ; Riguzzi, Fabrizio 4   VIAFID ORCID Logo 

1  Department of Environmental and Prevention Sciences, University of Ferrara, Ferrara, Italy (e-mail: [email protected] ) 
2  Department of Engineering, University of Ferrara, Ferrara, Italy (e-mail: [email protected] ) 
3  TU Wien, Wien, Austria (e-mail: [email protected] ) 
4  Department of Mathematics and Computer Science, University of Ferrara, Ferrara, Italy (e-mail: [email protected] ) 
Pages
33-63
Section
Original Article
Publication year
2025
Publication date
Jan 2025
Publisher
Cambridge University Press
ISSN
14710684
e-ISSN
14753081
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1017/S1471068424000474
ProQuest document ID
3166674311
Copyright
© The Author(s), 2025. Published by Cambridge University Press. This work is licensed under the Creative Commons Attribution License This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.