Search Results for author:
Found 2 papers, 1 papers with code
Analyzing Generalization in Policy Networks: A Case Study with the Double-Integrator System
Extensive utilization of deep reinforcement learning (DRL) policy networks in diverse continuous control tasks has raised questions regarding performance degradation in expansive state spaces where the input state norm is larger than that in the training environment.
Reinforcement Learning by Guided Safe Exploration
Drawing from transfer learning, we also regularize a target policy (the student) towards the guide while the student is unreliable and gradually eliminate the influence of the guide as training progresses.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
