Reinforcement knowledge graph reasoning based on dual agents and attention mechanism: X.-H. Yang et al.
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XH Yang, T Wang, JS Gan, LY Gao, GF Ma…
Applied Intelligence, 2025
Springer
Reinforcement learning can model knowledge graph multi-hop reasoning as Markov Decision Processes and improve the accuracy and interpretability of predicting paths between entities. Existing reasoning methods usually ignore the logic of action selection when facing one-to-many or many-to-many relationships, resulting in poor performance in knowledge graph reasoning. Furthermore, the general multi-hop reasoning only achieves effective short-path reasoning and lacks efficiency in long-distance reasoning. To address …
