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Hi, thanks for the great work of text game. I have one question about the RL agent. In this paper, your agent is Deep Reinforcement Relevance Network (DRRN) from ACL2016 paper. I am wondering did you ever conduct some preliminary experiments on more powerful encoding function like BERT for better contextualized word embedding ? Do you have some intuition for making Transformer as Q-network in DRL ? Much Thanks !
The text was updated successfully, but these errors were encountered:
Hannibal046
changed the title
Any try on other encoding function ?
Any try on other RL agent ?
Aug 7, 2022
Hi, thanks for the great work of text game. I have one question about the RL agent. In this paper, your agent is Deep Reinforcement Relevance Network (DRRN) from ACL2016 paper. I am wondering did you ever conduct some preliminary experiments on more powerful encoding function like BERT for better contextualized word embedding ? Do you have some intuition for making Transformer as Q-network in DRL ? Much Thanks !
The text was updated successfully, but these errors were encountered: