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Found 2 papers, 1 papers with code
Reward-Machine-Guided, Self-Paced Reinforcement Learning
Self-paced reinforcement learning (RL) aims to improve the data efficiency of learning by automatically creating sequences, namely curricula, of probability distributions over contexts.
Joint Learning of Reward Machines and Policies in Environments with Partially Known Semantics
We develop a reinforcement-learning algorithm that infers a reward machine that encodes the underlying task while learning how to execute it, despite the uncertainties of the propositions' truth values.
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