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Found 3 papers, 2 papers with code
Monitored Markov Decision Processes
In this paper, we formalize a novel but general RL framework - Monitored MDPs - where the agent cannot always observe rewards.
Learning to Be Cautious
An agent that could learn to be cautious would overcome this challenge by discovering for itself when and how to behave cautiously.
Transfer Learning for Prosthetics Using Imitation Learning
In this paper, We Apply Reinforcement learning (RL) techniques to train a realistic biomechanical model to work with different people and on different walking environments.
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