Is Long Horizon Reinforcement Learning More Difficult Than Short Horizon Reinforcement Learning?

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Abstract:

Learning to plan for long horizons is a central challenge in episodic reinforcement learning problems. A fundamental question is to understand how the difficulty of the problem scales as the horizon increases. Here the natural measure of sample complexity is a normalized one: we are interested in the number of episodes it takes to prova...More

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