Submitted by smallest_meta_review t3_yng63w in MachineLearning
luchins t1_ivbuz90 wrote
Reply to comment by smallest_meta_review in [R] Reincarnating Reinforcement Learning (NeurIPS 2022) - Google Brain by smallest_meta_review
> I feel it's going one step further and saying why not reuse prior computational work (e.g., existing learned agents) in the same problem
could you make me an example please? I don't get what you mean with using agents with different architectures
smallest_meta_review OP t1_ivcghme wrote
Oh, so one of the examples in the blog post is that we start with a DQN agent with a 3-layer CNN architecture and reincarnate another Rainbow agent with a ResNet architecture (Impala-CNN) using the QDagger approach for reincarnation. Once reincarnated, the ResNet Rainbow agent is further trained with RL to maximize reward. See the paper here for more details: https://openreview.net/forum?id=t3X5yMI_4G2
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