Deep Reinforcement Learning for Dexterous Manipulation with Concept Networks

no code implementations • 20 Sep 2017 • Aditya Gudimella, Ross Story, Matineh Shaker, Ruofan Kong, Matthew Brown, Victor Shnayder, Marcos Campos

Deep reinforcement learning yields great results for a large array of problems, but models are generally retrained anew for each new problem to be solved.

Problem Decomposition reinforcement-learning +1