From the 1 of 4 linked papers with an AI index.
4 papers
On the Policy Convergence of Policy Mirror Descent Methods
Wenye Li, Ke Wei
The paper provides a unified convergence analysis for unregularized policy mirror descent with constant step sizes in finite discounted Markov decision processes, covering a wide r…
Policy Mirror Descent with Temporal Difference Learning: Sample Complexity under Online Markov Data
Wenye Li, Hongxu Chen, Jiacai Liu +1
This paper studies the policy mirror descent (PMD) method, which is a general policy optimization framework in reinforcement learning and can cover a wide range of policy gradient…
On the Convergence of Policy Mirror Descent with Temporal Difference Evaluation
Jiacai Liu, Wenye Li, Ke Wei
Policy mirror descent (PMD) is a general policy optimization framework in reinforcement learning, which can cover a wide range of typical policy optimization methods by specifying…
S-NeRF++: Autonomous Driving Simulation via Neural Reconstruction and Generation
Yurui Chen, Junge Zhang, Ziyang Xie +4
Autonomous driving simulation system plays a crucial role in enhancing self-driving data and simulating complex and rare traffic scenarios, ensuring navigation safety. However, tra…