Exploration by Maximizing R\'enyi Entropy for Zero-Shot Meta RL

Zhang Chuheng
Zhang Chuheng
Cai Yuanying
Cai Yuanying
Li Jian
Li Jian
Cited by: 0|Views10

Abstract:

Exploring the transition dynamics is essential to the success of reinforcement learning (RL) algorithms. To face the challenges of exploration, we consider a zero-shot meta RL framework that completely separates exploration from exploitation and is suitable for the meta RL setting where there are many reward functions of interest. In th...More

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