State Space Decomposition and Subgoal Creation for Transfer in Deep Reinforcement Learning

Typical reinforcement learning (RL) agents learn to complete tasks specified by reward functions tailored to their domain. As such, the policies they learn do not generalize even to similar domains... (read more)

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