For questions related to imitation learning (IL), a reinforcement learning technique where a policy is learned from examples (represented as trajectories) of an (optimal) agent's behavior. IL is similar to inverse reinforcement learning (IRL), where a reward function is learned from examples of the (optimal) agent's behavior, which can then be used to solve the RL problem (i.e. find the policy).
Questions tagged [imitation-learning]
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How to decide size of generated dataset in DAGGER agorithm
In the DAGGER algorithm, how does one determine the number of samples required for one iteration of the training loop?
Looking at the picture above, I understand initially, during the 1st iteration, the dataset D comes from pre-recorded samples and…
RoyJ
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