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The computational complexity of single-player imperfect-recall games

Abstract:
We study single-player extensive-form games with imperfect recall, such as the Sleeping Beauty problem or the Absentminded Driver game. For such games, two natural equilibrium concepts have been proposed as alternative solution concepts to ex-ante optimality. One equilibrium concept uses generalized double halving (GDH) as a belief system and evidential decision theory (EDT), and another one uses generalized thirding (GT) as a belief system and causal decision theory (CDT). Our findings relate those three solution concepts of a game to solution concepts of a polynomial maximization problem: global optima, optimal points with respect to subsets of variables and Karush-Kuhn-Tucker (KKT) points. Based on these correspondences, we are able to settle various complexity-theoretic questions on the computation of such strategies. For ex-ante optimality and (EDT,GDH)-equilibria, we obtain NP-hardness and inapproximability, and for (CDT,GT)-equilibria we obtain CLS-completeness results.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.24963/ijcai.2023/321

Authors

More by this author
Institution:
University of Oxford
Division:
HUMS
Department:
Philosophy
Role:
Author
ORCID:
0000-0003-1899-7884
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
ORCID:
0000-0002-5436-7890


Publisher:
International Joint Conferences on Artificial Intelligence
Host title:
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence
Pages:
2878-2887
Publication date:
2023-08-11
Acceptance date:
2023-05-19
Event title:
32nd IJCAI International Joint Conference on Artificial Intelligence (IJCAI 2023)
Event location:
Macao, SAR
Event website:
https://ijcai-23.org/
Event start date:
2023-08-19
Event end date:
2023-08-25
DOI:
ISSN:
1045-0823
EISBN:
9781956792034


Language:
English
Pubs id:
1522002
Local pid:
pubs:1522002
Deposit date:
2026-08-11
ARK identifier:

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