Venue: NeurIPS 2022 Workshop Offline_RL

Reviews:

final_score: rating: 7: Good paper, accept
review_content: This paper introduced a hybrid RL setting where an offline RL agent has the access to interact with the environment. This paper further proposed a variant of the classical Q-iteration algorithm, named Hy-Q, for the hybrid setting. Overall, this paper discussed an important setting which has received less attention in the community, and provided some interesting results.

Pros:
- This paper proves some theoretical advantages of Hy-Q.
- Hy-Q can improve the sample efficiency of online RL.

Cons:
- Hy-Q is only tested in one complex Atari game.
- As mentioned in line90, I am curious about how would the size of offline dataset affect Hy-Q.
review_title: An interesting theoretical work for a hybrid RL setting.

Decision: Accept