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cs.AI2026
Synthesizing POMDP Policies: Sampling Meets Model-checking via Learning
Debraj Chakraborty, Anirban Majumdar, Prince Mathew +2
Partially Observable Markov Decision Processes (POMDPs) are the standard framework for decision-making under uncertainty. While sampling-based methods scale well, they lack formal…
cs.AI2025
About Time: Model-free Reinforcement Learning with Timed Reward Machines
Rajarshi Roy, Anirban Majumdar, Ritam Raha +2
Reward specification plays a central role in reinforcement learning (RL), guiding the agent's behavior. To express non-Markovian rewards, formalisms such as reward machines have be…