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Found 3 papers, 1 papers with code
Task-Agnostic Exploration via Policy Gradient of a Non-Parametric State Entropy Estimate
In a reward-free environment, what is a suitable intrinsic objective for an agent to pursue so that it can learn an optimal task-agnostic exploration policy?
An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies
What is a good exploration strategy for an agent that interacts with an environment in the absence of external rewards?
Configurable Markov Decision Processes
After having introduced our approach and derived some theoretical results, we present the experimental evaluation in two explicative problems to show the benefits of the environment configurability on the performance of the learned policy.
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