activity
20182022
most citedRobotic Surveillance Based on the Meeting Time of Random Walks

2 citations · 4 across the 7 of their papers we have counts for

collaborators

10 papers

cs.GT2022

Evaluation and Learning in Two-Player Symmetric Games via Best and Better Responses

Rui Yan, Weixian Zhang, Ruiliang Deng +3

Artificial intelligence and robotic competitions are accompanied by a class of game paradigms in which each player privately commits a strategy to a game system which simulates the…

cs.IT2021

Privacy-Utility Trade-Offs Against Limited Adversaries

Xiaoming Duan, Zhe Xu, Rui Yan +1

We study privacy-utility trade-offs where users share privacy-correlated useful information with a service provider to obtain some utility. The service provider is adversarial in t…

eess.SY2021

Robust Pandemic Control Synthesis with Formal Specifications: A Case Study on COVID-19 Pandemic

Zhe Xu, Xiaoming Duan

Pandemics can bring a range of devastating consequences to public health and the world economy. Identifying the most effective control strategies has been the imperative task all a…

math.OC20201 cited

Stochastic Strategies for Robotic Surveillance as Stackelberg Games

Xiaoming Duan, Dario Paccagnan, Francesco Bullo

This paper studies a stochastic robotic surveillance problem where a mobile robot moves randomly on a graph to capture a potential intruder that strategically attacks a location on…

math.OC20201 cited

Markov Chain-Based Stochastic Strategies for Robotic Surveillance

Xiaoming Duan, Francesco Bullo

This article surveys recent advancements of strategy designs for persistent robotic surveillance tasks with the focus on stochastic approaches. The problem describes how mobile rob…

cs.GT2020

Policy Evaluation and Seeking for Multi-Agent Reinforcement Learning via Best Response

Rui Yan, Xiaoming Duan, Zongying Shi +3

This paper introduces two metrics (cycle-based and memory-based metrics), grounded on a dynamical game-theoretic solution concept called sink equilibrium, for the evaluation, ranki…