3 papers
cs.AI2025
Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning
Xinsong Feng, Zihan Yu, Yanhai Xiong +1
Reinforcement learning (RL) has emerged as a promising tool for combinatorial optimization (CO) problems due to its ability to learn fast, effective, and generalizable solutions. N…
cs.GT2025
Can Reinforcement Learning Solve Asymmetric Combinatorial-Continuous Zero-Sum Games?
Yuheng Li, Panpan Wang, Haipeng Chen
There have been extensive studies on learning in zero-sum games, focusing on the analysis of the existence and algorithmic convergence of Nash equilibrium (NE). Existing studies ma…
cs.AI2024
Focused ReAct: Improving ReAct through Reiterate and Early Stop
Shuoqiu Li, Han Xu, Haipeng Chen
Large language models (LLMs) have significantly improved their reasoning and decision-making capabilities, as seen in methods like ReAct. However, despite its effectiveness in tack…