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20172025
most citedOff-Policy Meta-Reinforcement Learning Based on Feature Embedding Spaces

2 citations · 3 across the 8 of their papers we have counts for

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cs.AI2017

Deep Reinforcement Learning for Inquiry Dialog Policies with Logical Formula Embeddings

Takuya Hiraoka, Masaaki Tsuchida, Yotaro Watanabe

This paper is the first attempt to learn the policy of an inquiry dialog system (IDS) by using deep reinforcement learning (DRL). Most IDS frameworks represent dialog states and di…