1 citations · 2 across the 12 of their papers we have counts for
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Initial Distribution Sensitivity of Constrained Markov Decision Processes
Alperen Tercan, Necmiye Ozay
Constrained Markov Decision Processes (CMDPs) are notably more complex to solve than standard MDPs due to the absence of universally optimal policies across all initial state distr…
Efficient Reward Identification In Max Entropy Reinforcement Learning with Sparsity and Rank Priors
Mohamad Louai Shehab, Alperen Tercan, Necmiye Ozay
In this paper, we consider the problem of recovering time-varying reward functions from either optimal policies or demonstrations coming from a max entropy reinforcement learning p…
Learning Reward Machines from Partially Observed Policies
Mohamad Louai Shehab, Antoine Aspeel, Necmiye Ozay
Inverse reinforcement learning is the problem of inferring a reward function from an optimal policy or demonstrations by an expert. In this work, it is assumed that the reward is e…