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Knowledge Graph Reasoning with Self-supervised Reinforcement Learning
May 24, 2024, 4:45 a.m. | Ying Ma, Owen Burns, Mingqiu Wang, Gang Li, Nan Du, Laurent El Shafey, Liqiang Wang, Izhak Shafran, Hagen Soltau
cs.LG updates on arXiv.org arxiv.org
Abstract: Reinforcement learning (RL) is an effective method of finding reasoning pathways in incomplete knowledge graphs (KGs). To overcome the challenges of a large action space, a self-supervised pre-training method is proposed to warm up the policy network before the RL training stage. To alleviate the distributional mismatch issue in general self-supervised RL (SSRL), in our supervised learning (SL) stage, the agent selects actions based on the policy network and learns from generated labels; this self-generation …
arxiv cs.ai cs.cl cs.lg graph knowledge knowledge graph reasoning reinforcement reinforcement learning type
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