@inproceedings{586c535f621f49de8a422c4e3ce05a40,
title = "Finding Optimal Deterministic Policies for Constrained Stochastic Shortest Path Problems",
abstract = "Constrained Stochastic Shortest Path problems (CSSPs) are a modelling framework for probabilistic problems with a primary cost and constraints over secondary costs such as fuel consumption or monetary budget.While the optimal solution for a CSSP is usually a stochastic policy, practical considerations often demand deterministic solutions, for instance, in aviation and multi-agent systems.Previous works have addressed this issue for special cases of CSSPs; in this work, we show the technical issues in generalising these results and show how they can be addressed.Then, using these methods, we extend the state-of-the-art heuristic search method for finding optimal stochastic policies to efficiently find deterministic policies for CSSPs.We show experimentally that our algorithm competes with the state-of-the-art, and is able to solve the class of problems with difficult-to-satisfy constraints on which the state-of-the-art fails.",
author = "Johannes Schmalz and Felipe Trevizan",
note = "Publisher Copyright: {\textcopyright} 2024 The Authors.; 27th European Conference on Artificial Intelligence, ECAI 2024 ; Conference date: 19-10-2024 Through 24-10-2024",
year = "2024",
month = oct,
day = "16",
doi = "10.3233/FAIA240986",
language = "English",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "4148--4156",
editor = "Ulle Endriss and Melo, {Francisco S.} and Kerstin Bach and Alberto Bugarin-Diz and Alonso-Moral, {Jose M.} and Senen Barro and Fredrik Heintz",
booktitle = "ECAI 2024 - 27th European Conference on Artificial Intelligence, Including 13th Conference on Prestigious Applications of Intelligent Systems, PAIS 2024, Proceedings",
address = "Netherlands",
}