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Despite significant progress in general AI planning, certain domains remainout of reach of current AI planning systems. Sokoban is a PSPACE-completeplanning task and represents one of the hardest domains for current AIplanners. Even domain-specific specialized search methods fail quickly due tothe exponential search complexity on hard instances. Our approach based on deepreinforcement learning augmented with a curriculum-driven method is the firstone to solve hard instances within one day of training while other modernsolvers cannot solve these instances within any reasonable time limit. Incontrast to prior efforts, which use carefully handcrafted pruning techniques,our approach automatically uncovers domain structure. Our results reveal thatdeep RL provides a promising framework for solving previously unsolved AIplanning problems, provided a proper training curriculum can be devised.

Solving Hard AI Planning Instances Using Curriculum-Driven Deep Reinforcement Learning