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cs.AI2026
Automating the Refinement of Reinforcement Learning Specifications
Tanmay Ambadkar, ÄorÄe ŽikeliÄ, Abhinav Verma
Logical specifications have been shown to help reinforcement learning algorithms in achieving complex tasks. However, when a task is under-specified, agents might fail to learn use…
cs.AI2024
Certified Policy Verification and Synthesis for MDPs under Distributional Reach-avoidance Properties
S. Akshay, Krishnendu Chatterjee, Tobias Meggendorfer +1
Markov Decision Processes (MDPs) are a classical model for decision making in the presence of uncertainty. Often they are viewed as state transformers with planning objectives defi…
cs.AI2024
Solving Long-run Average Reward Robust MDPs via Stochastic Games
Krishnendu Chatterjee, Ehsan Kafshdar Goharshady, Mehrdad Karrabi +2
Markov decision processes (MDPs) provide a standard framework for sequential decision making under uncertainty. However, MDPs do not take uncertainty in transition probabilities in…