Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path

3 Mar 2020Kei OtaYoko SasakiDevesh K. JhaYusuke YoshiyasuAsako Kanezaki

In this paper, we consider the problem of building learning agents that can efficiently learn to navigate in constrained environments. The main goal is to design agents that can efficiently learn to understand and generalize to different environments using high-dimensional inputs (a 2D map), while following feasible paths that avoid obstacles in obstacle-cluttered environment... (read more)

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