Interpretable Reinforcement Learning for Robotics and Continuous Control
The paper proposes Interpretable Continuous Control Trees (ICCTs), a tree-based model that can be optimized using modern, gradient-based, reinforcement learning approaches to produce high-performing, interpretable policies. The ICCTs show potential…
Continue reading