A comparison of direct and model-based reinforcement learning 论文

2002引用 242
Reinforcement Learning in RoboticsEvolutionary Algorithms and ApplicationsAdaptive Dynamic Programming Control

摘要

This paper compares direct reinforcement learning (no explicit model) and model-based reinforcement learning on a simple task: pendulum swing up. We find that in this task model-based approaches support reinforcement learning from smaller amounts of training data and efficient handling of changing goals.