57 citations · 123 across the 7 of their papers we have counts for
4 papers · 1 filter
MiniOpt: Reasoning to Model and Solve General Optimization Problems with Limited Resources
Ke Zhao, Zixiang Di, Hong Qian +9
Achieving strong optimization generalization across diverse optimization problems while requiring limited training resources remains a challenging problem for optimization-oriented…
Unified Policy Optimization for Continuous-action Reinforcement Learning in Non-stationary Tasks and Games
Rong-Jun Qin, Fan-Ming Luo, Hong Qian +1
This paper addresses policy learning in non-stationary environments and games with continuous actions. Rather than the classical reward maximization mechanism, inspired by the idea…
Derivative-Free Reinforcement Learning: A Review
Hong Qian, Yang Yu
Reinforcement learning is about learning agent models that make the best sequential decisions in unknown environments. In an unknown environment, the agent needs to explore the env…
ZOOpt: Toolbox for Derivative-Free Optimization
Yu-Ren Liu, Yi-Qi Hu, Hong Qian +2
Recent advances in derivative-free optimization allow efficient approximation of the global-optimal solutions of sophisticated functions, such as functions with many local optima,…