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Andrew Wagenmaker

@ajwagenmaker • 1,310 subscribers

MTS @physical_int | Incoming Assistant Professor @UTAustin CS | Previously: Postdoc @Berkeley_EECS, PhD @uwcse

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How should we pretrain a policy from demonstrations to ensure it is an effective initialization for RL finetuning, while preserving the performance of the pretrained policy itself? We propose Posterior Behavioral Cloning (PostBC)! (1/11)
1:05
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How should we pretrain a policy from demonstrations to ensure it is an effective initialization for RL finetuning, while preserving the performance of the pretrained policy itself? We propose Posterior Behavioral Cloning (PostBC)! (1/11)

Andrew Wagenmaker

60,181 просмотров • 9 месяцев назад

Diffusion policies have demonstrated impressive performance in robot control, yet are difficult to improve online when 0-shot performance isn’t enough. To address this challenge, we introduce DSRL: Diffusion Steering via Reinforcement Learning. (1/n)
2:53
ajwagenmaker's profile picture

Diffusion policies have demonstrated impressive performance in robot control, yet are difficult to improve online when 0-shot performance isn’t enough. To address this challenge, we introduce DSRL: Diffusion Steering via Reinforcement Learning. (1/n)

Andrew Wagenmaker

65,162 просмотров • 1 год назад

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