3 papers
cs.LG2024
ELO-Rated Sequence Rewards: Advancing Reinforcement Learning Models
Qi Ju, Falin Hei, Zhemei Fang +1
Reinforcement Learning (RL) heavily relies on the careful design of the reward function. However, accurately assigning rewards to each state-action pair in Long-Term Reinforcement…
cs.GT2024
From First-Order to Second-Order Rationality: Advancing Game Convergence with Dynamic Weighted Fictitious Play
Qi Ju, Falin Hei, Yuxuan Liu +2
Constructing effective algorithms to converge to Nash Equilibrium (NE) is an important problem in algorithmic game theory. Prior research generally posits that the upper bound on t…
cs.AI2023
Accelerating Nash Equilibrium Convergence in Monte Carlo Settings Through Counterfactual Value Based Fictitious Play
Ju Qi, Falin Hei, Ting Feng +3
Counterfactual Regret Minimization (CFR) and its variants are widely recognized as effective algorithms for solving extensive-form imperfect information games. Recently, many impro…