Graph-Structured Policy Learning for Multi-Goal Manipulation Tasks
David Klee,Ondrej Biza,Robert Platt,David Klee,Ondrej Biza,Robert Platt
Multi-goal policy learning for robotic manipu-lation is challenging. Prior successes have used state-based representations of the objects or provided demonstration data to facilitate learning. In this paper, by hand-coding a high-level discrete representation of the domain, we show that policies to reach dozens of goals can be learned with a single network using Q-learning from pixels. The agent f...
