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Combining Subgoal Graphs with Reinforcement Learning to Build a Rational Pathfinder
The first advantage of the proposed method is that SSG can solve the limitations of sparse reward and local minima trap for RL agents; thus, LSPI can be used to generate paths in complex environments.
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