6 citations · 11 across the 2 of their papers we have counts for
3 papers
Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons
Anthony Liang, Yigit Korkmaz, Jiahui Zhang +14
General-purpose robot reward models are typically trained to predict absolute task progress from expert demonstrations, providing only local, frame-level supervision. While effecti…
Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment
Michael Chang, Sidhant Kaushik, Sergey Levine +1
Many transfer problems require re-using previously optimal decisions for solving new tasks, which suggests the need for learning algorithms that can modify the mechanisms for choos…
Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions
Michael Chang, Sidhant Kaushik, S. Matthew Weinberg +2
This paper seeks to establish a framework for directing a society of simple, specialized, self-interested agents to solve what traditionally are posed as monolithic single-agent se…