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Found 4 papers, 2 papers with code
Guided Exploration in Reinforcement Learning via Monte Carlo Critic Optimization
We address these challenges by proposing a novel guided exploration method that uses a differential directional controller to incorporate scalable exploratory action correction.
Solving Continuous Control with Episodic Memory
The application of episodic memory for continuous control with a large action space is not trivial.
Interpretable Few-Shot Learning via Linear Distillation
It is important to develop mathematically tractable models than can interpret knowledge extracted from the data and provide reasonable predictions.
Conditioning of Reinforcement Learning Agents and its Policy Regularization Application
In this paper, we try to answer the following question: Can information about policy conditioning help to shape a more stable and general policy of reinforcement learning agents?
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