27 citations · 78 across the 13 of their papers we have counts for
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cs.AI2022★ 9 cited
An Efficient Dynamic Sampling Policy For Monte Carlo Tree Search
Gongbo Zhang, Yijie Peng, Yilong Xu
We consider the popular tree-based search strategy within the framework of reinforcement learning, the Monte Carlo Tree Search (MCTS), in the context of finite-horizon Markov decis…
cs.LG2022★ 1 cited
Quantile-Based Policy Optimization for Reinforcement Learning
Jinyang Jiang, Jiaqiao Hu, Yijie Peng
Classical reinforcement learning (RL) aims to optimize the expected cumulative rewards. In this work, we consider the RL setting where the goal is to optimize the quantile of the c…
cs.GT2022★ 1 cited
Efficient Distributed Learning in Stochastic Non-cooperative Games without Information Exchange
Haidong Li, Anzhi Sheng, Yijie Peng +1
In this work, we study stochastic non-cooperative games, where only noisy black-box function evaluations are available to estimate the cost function for each player. Since each pla…