RACER: Reinforced Agent Collaboration for Explainable Reasoning on Knowledge Graphs
RACER employs a semantic-aware action pruning and teacher-guided reinforcement learning mechanism to efficiently extract high-quality reasoning pathways from large-scale KGs, and introduces a cross-task accumulated shared memory graph paired with an attention-driven multi-path knowledge refinement module.
Yuwei Lou, Hao Hu, Yu-Zhou Jiang et al.
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