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Ryosuke Kohita

1 accepted papers

2021

Neuro-Symbolic Reinforcement Learning with First-Order Logic

EMNLP 2021main

Deep reinforcement learning (RL) methods often require many trials before convergence, and no direct interpretability of trained policies is provided. In order to achieve fast convergence and interpretability for the policy in RL, we propose a novel RL method for text-based games with a recent neuro…

Cited by 48SourcePDFScholar