Empowerment-driven Exploration using Mutual Information Estimation

11 Oct 2018Navneet Madhu Kumar

However, many of the state of the art deep reinforcement learning algorithms, that rely on epsilon-greedy, fail on these environments. We formulate empowerment as the channel capacity between states and actions and is calculated by estimating the mutual information between the actions and the following states. We demonstrate that an empowerment driven agent is able to improve significantly the score of a baseline DQN agent on the game of Montezuma's Revenge.

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