Limit-sure reachability for small memory policies in POMDPs is NP-complete
Asadi A, Chatterjee K, Saona Urmeneta RJ, Shafiee A. 2025. Limit-sure reachability for small memory policies in POMDPs is NP-complete. The 41st Conference on Uncertainty in Artificial Intelligence. UAI: Conference on Uncertainty in Artificial Intelligence, PMLR, vol. 286, 238–247.
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Series Title
PMLR
Abstract
A standard model that arises in several applications in sequential decision-making is partially observable Markov decision processes (POMDPs) where a decision-making agent interacts with an uncertain environment. A basic objective in POMDPs is the reachability objective, where given a target set of states, the goal is to eventually arrive at one of them.
The limit-sure problem asks whether reachability can be ensured with probability arbitrarily close to 1. In general, the limit-sure reachability problem for POMDPs is undecidable. However, in many practical cases, the most relevant question is the existence of policies with a small amount of memory. In this work, we study the limit-sure reachability problem for POMDPs with a fixed amount of memory. We establish that the computational complexity of the problem is NP-complete.
Publishing Year
Date Published
2025-07-01
Proceedings Title
The 41st Conference on Uncertainty in Artificial Intelligence
Publisher
ML Research Press
Acknowledgement
This research was partially supported by Austrian Science Fund (FWF) 10.55776/COE12, the support of the French Agence Nationale de la Recherche (ANR) under reference ANR-21-CE40-0020 (CONVERGENCE project), and the ERC CoG 863818 (ForM-SMArt) grant.
Volume
286
Page
238-247
Conference
UAI: Conference on Uncertainty in Artificial Intelligence
Conference Location
Rio de Janeiro, Brazil
Conference Date
2025-07-21 – 2025-07-25
eISSN
IST-REx-ID
Cite this
Asadi A, Chatterjee K, Saona Urmeneta RJ, Shafiee A. Limit-sure reachability for small memory policies in POMDPs is NP-complete. In: The 41st Conference on Uncertainty in Artificial Intelligence. Vol 286. ML Research Press; 2025:238-247.
Asadi, A., Chatterjee, K., Saona Urmeneta, R. J., & Shafiee, A. (2025). Limit-sure reachability for small memory policies in POMDPs is NP-complete. In The 41st Conference on Uncertainty in Artificial Intelligence (Vol. 286, pp. 238–247). Rio de Janeiro, Brazil: ML Research Press.
Asadi, Ali, Krishnendu Chatterjee, Raimundo J Saona Urmeneta, and Ali Shafiee. “Limit-Sure Reachability for Small Memory Policies in POMDPs Is NP-Complete.” In The 41st Conference on Uncertainty in Artificial Intelligence, 286:238–47. ML Research Press, 2025.
A. Asadi, K. Chatterjee, R. J. Saona Urmeneta, and A. Shafiee, “Limit-sure reachability for small memory policies in POMDPs is NP-complete,” in The 41st Conference on Uncertainty in Artificial Intelligence, Rio de Janeiro, Brazil, 2025, vol. 286, pp. 238–247.
Asadi A, Chatterjee K, Saona Urmeneta RJ, Shafiee A. 2025. Limit-sure reachability for small memory policies in POMDPs is NP-complete. The 41st Conference on Uncertainty in Artificial Intelligence. UAI: Conference on Uncertainty in Artificial Intelligence, PMLR, vol. 286, 238–247.
Asadi, Ali, et al. “Limit-Sure Reachability for Small Memory Policies in POMDPs Is NP-Complete.” The 41st Conference on Uncertainty in Artificial Intelligence, vol. 286, ML Research Press, 2025, pp. 238–47.
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