most citedBlocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning

4 citations · 5 across the 2 of their papers we have counts for

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cs.LG2021★ 1 cited

Braxlines: Fast and Interactive Toolkit for RL-driven Behavior Engineering beyond Reward Maximization

Shixiang Shane Gu, Manfred Diaz, Daniel C. Freeman +7

The goal of continuous control is to synthesize desired behaviors. In reinforcement learning (RL)-driven approaches, this is often accomplished through careful task reward engineer…