327 citations · 970 across the 56 of their papers we have counts for
10 papers · 1 filter
Towards Understanding Asynchronous Advantage Actor-critic: Convergence and Linear Speedup
Han Shen, Kaiqing Zhang, Mingyi Hong +1
Asynchronous and parallel implementation of standard reinforcement learning (RL) algorithms is a key enabler of the tremendous success of modern RL. Among many asynchronous RL algo…
First observation of laser-beam interaction in a dipole magnet
Jiawei Yan, Nanshun Huang, Haixiao Deng +3
As a new-generation light source, free-electron lasers (FELs) provide high-brightness X-ray pulses at the angstrom-femtosecond space and time scales. The fundamental physics behind…
Self-Amplification of Coherent Energy Modulation in Seeded Free-Electron Lasers
Jiawei Yan, Zhangfeng Gao, Zheng Qi +23
The spectroscopic techniques for time-resolved fine analysis of matter require coherent X-ray radiation with femtosecond duration and high average brightness. Seeded free-electron…
Model-Free Non-Stationary RL: Near-Optimal Regret and Applications in Multi-Agent RL and Inventory Control
Weichao Mao, Kaiqing Zhang, Ruihao Zhu +2
We consider model-free reinforcement learning (RL) in non-stationary Markov decision processes. Both the reward functions and the state transition functions are allowed to vary arb…
Reinforcement Learning in Non-Stationary Discrete-Time Linear-Quadratic Mean-Field Games
Muhammad Aneeq uz Zaman, Kaiqing Zhang, Erik Miehling +1
In this paper, we study large population multi-agent reinforcement learning (RL) in the context of discrete-time linear-quadratic mean-field games (LQ-MFGs). Our setting differs fr…
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity
Kaiqing Zhang, Sham M. Kakade, Tamer Başar +1
Model-based reinforcement learning (RL), which finds an optimal policy using an empirical model, has long been recognized as one of the corner stones of RL. It is especially suitab…