Knowledge Graph Reasoning with Self-supervised Reinforcement Learning

arXiv:2405.13640v1 Announce Type: cross
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