Self-Organizing Perceptual and Temporal Abstraction for Robot Reinforcement Learning

Abstract

A major current challenge in reinforcement learning research is to extend methods that work well on discrete, short-range, low-dimensional problems to continuous, highdiameter, high-dimensional problems, such as robot navigation using high-resolution sensors. We present a method whereby an robot in a continuous world can, with little prior knowledge of its… (More)

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