activity
20192021
most citedDiscovering Diverse Multi-Agent Strategic Behavior via Reward Randomization

13 citations · 15 across the 4 of their papers we have counts for

collaborators

5 papers

cs.MA2021

Temporal Induced Self-Play for Stochastic Bayesian Games

Weizhe Chen, Zihan Zhou, Yi Wu +1

One practical requirement in solving dynamic games is to ensure that the players play well from any decision point onward. To satisfy this requirement, existing efforts focus on eq…

cs.AI2021

Near-Optimal Reviewer Splitting in Two-Phase Paper Reviewing and Conference Experiment Design

Steven Jecmen, Hanrui Zhang, Ryan Liu +3

Many scientific conferences employ a two-phase paper review process, where some papers are assigned additional reviewers after the initial reviews are submitted. Many conferences a…

cs.AI202113 cited

Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization

Zhenggang Tang, Chao Yu, Boyuan Chen +6

We propose a simple, general and effective technique, Reward Randomization for discovering diverse strategic policies in complex multi-agent games. Combining reward randomization a…

cs.LG20202 cited

Deep Archimedean Copulas

Chun Kai Ling, Fei Fang, J. Zico Kolter

A central problem in machine learning and statistics is to model joint densities of random variables from data. Copulas are joint cumulative distribution functions with uniform mar…

cs.MA2019

Signal Instructed Coordination in Cooperative Multi-agent Reinforcement Learning

Liheng Chen, Hongyi Guo, Yali Du +7

In many real-world problems, a team of agents need to collaborate to maximize the common reward. Although existing works formulate this problem into a centralized learning with dec…