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cs.AI2026★ 1 cited
Finite-State Controllers for (Hidden-Model) POMDPs using Deep Reinforcement Learning
David Hudák, Maris F. L. Galesloot, Martin Tappler +3
Solving partially observable Markov decision processes (POMDPs) requires computing policies under imperfect state information. Despite recent advances, the scalability of existing…
cs.AI2024
Threshold UCT: Cost-Constrained Monte Carlo Tree Search with Pareto Curves
Martin Kurečka, Václav Nevyhoštěný, Petr Novotný +1
Constrained Markov decision processes (CMDPs), in which the agent optimizes expected payoffs while keeping the expected cost below a given threshold, are the leading framework for…