Abstract:The aim of path planning is to search for a path from the starting point to the goal. Numerous studies, however, have dealt with a single predefined goal. That is, an agent who has completed learning cannot reach other goals that have not been visited in the training. In the present study, we propose a novel reinforcement learning (RL) framework for an agent reachable to any subgoal as well as the final goal in path planning. To do this, we utilize goal-conditioned RL and propose bidirectional memory editing t… Show more
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