Paper

Actor-Critic for Linearly-Solvable Continuous MDP with Partially Known Dynamics

In many robotic applications, some aspects of the system dynamics can be modeled accurately while others are difficult to obtain or model. We present a novel reinforcement learning (RL) method for continuous state and action spaces that learns with partial knowledge of the system and without active exploration... (read more)

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