68 citations · 226 across the 24 of their papers we have counts for
25 papers
Testing for Reviewer Anchoring in Peer Review: A Randomized Controlled Trial
Ryan Liu, Steven Jecmen, Vincent Conitzer +2
Peer review frequently follows a process where reviewers first provide initial reviews, authors respond to these reviews, then reviewers update their reviews based on the authors'…
MABL: Bi-Level Latent-Variable World Model for Sample-Efficient Multi-Agent Reinforcement Learning
Aravind Venugopal, Stephanie Milani, Fei Fang +1
Multi-agent reinforcement learning (MARL) methods often suffer from high sample complexity, limiting their use in real-world problems where data is sparse or expensive to collect.…
Inverse Game Theory for Stackelberg Games: the Blessing of Bounded Rationality
Jibang Wu, Weiran Shen, Fei Fang +1
Optimizing strategic decisions (a.k.a. computing equilibrium) is key to the success of many non-cooperative multi-agent applications. However, in many real-world situations, we may…
Ranked Prioritization of Groups in Combinatorial Bandit Allocation
Lily Xu, Arpita Biswas, Fei Fang +1
Preventing poaching through ranger patrols protects endangered wildlife, directly contributing to the UN Sustainable Development Goal 15 of life on land. Combinatorial bandits have…
Fighting the Fog: Evaluating the Clarity of Privacy Disclosures in the Age of CCPA
Rex Chen, Fei Fang, Thomas Norton +2
Vagueness and ambiguity in privacy policies threaten the ability of consumers to make informed choices about how businesses collect, use, and share their personal information. The…
Robust Reinforcement Learning Under Minimax Regret for Green Security
Lily Xu, Andrew Perrault, Fei Fang +2
Green security domains feature defenders who plan patrols in the face of uncertainty about the adversarial behavior of poachers, illegal loggers, and illegal fishers. Importantly,…
Dual-Mandate Patrols: Multi-Armed Bandits for Green Security
Lily Xu, Elizabeth Bondi, Fei Fang +3
Conservation efforts in green security domains to protect wildlife and forests are constrained by the limited availability of defenders (i.e., patrollers), who must patrol vast are…
Bandit Data-Driven Optimization
Zheyuan Ryan Shi, Zhiwei Steven Wu, Rayid Ghani +1
Applications of machine learning in the non-profit and public sectors often feature an iterative workflow of data acquisition, prediction, and optimization of interventions. There…
Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments
Steven Jecmen, Hanrui Zhang, Ryan Liu +3
We consider three important challenges in conference peer review: (i) reviewers maliciously attempting to get assigned to certain papers to provide positive reviews, possibly as pa…
Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning
Qian Long, Zihan Zhou, Abhibav Gupta +3
In multi-agent games, the complexity of the environment can grow exponentially as the number of agents increases, so it is particularly challenging to learn good policies when the…
Green Security Game with Community Engagement
Taoan Huang, Weiran Shen, David Zeng +3
While game-theoretic models and algorithms have been developed to combat illegal activities, such as poaching and over-fishing, in green security domains, none of the existing work…
Artificial Intelligence for Social Good: A Survey
Zheyuan Ryan Shi, Claire Wang, Fei Fang
Artificial intelligence for social good (AI4SG) is a research theme that aims to use and advance artificial intelligence to address societal issues and improve the well-being of th…
AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline
Andrew Perrault, Fei Fang, Arunesh Sinha +1
With the maturing of AI and multiagent systems research, we have a tremendous opportunity to direct these advances towards addressing complex societal problems. In pursuit of this…
Efficient Regret Minimization Algorithm for Extensive-Form Correlated Equilibrium
Gabriele Farina, Chun Kai Ling, Fei Fang +1
Self-play methods based on regret minimization have become the state of the art for computing Nash equilibria in large two-players zero-sum extensive-form games. These methods fund…
Dynamic Trip-Vehicle Dispatch with Scheduled and On-Demand Requests
Taoan Huang, Bohui Fang, Xiaohui Bei +1
Transportation service providers that dispatch drivers and vehicles to riders start to support both on-demand ride requests posted in real time and rides scheduled in advance, lead…
Correlation in Extensive-Form Games: Saddle-Point Formulation and Benchmarks
Gabriele Farina, Chun Kai Ling, Fei Fang +1
While Nash equilibrium in extensive-form games is well understood, very little is known about the properties of extensive-form correlated equilibrium (EFCE), both from a behavioral…
Learning and Planning in the Feature Deception Problem
Zheyuan Ryan Shi, Ariel D. Procaccia, Kevin S. Chan +5
Today's high-stakes adversarial interactions feature attackers who constantly breach the ever-improving security measures. Deception mitigates the defender's loss by misleading the…
Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games
Chun Kai Ling, Fei Fang, J. Zico Kolter
With the recent advances in solving large, zero-sum extensive form games, there is a growing interest in the inverse problem of inferring underlying game parameters given only acce…
Artificial Intelligence for Social Good
Gregory D. Hager, Ann Drobnis, Fei Fang +8
The Computing Community Consortium (CCC), along with the White House Office of Science and Technology Policy (OSTP), and the Association for the Advancement of Artificial Intellige…
Draining the Water Hole: Mitigating Social Engineering Attacks with CyberTWEAK
Zheyuan Ryan Shi, Aaron Schlenker, Brian Hay +5
Cyber adversaries have increasingly leveraged social engineering attacks to breach large organizations and threaten the well-being of today's online users. One clever technique, th…
On the Inducibility of Stackelberg Equilibrium for Security Games
Qingyu Guo, Jiarui Gan, Fei Fang +3
Strong Stackelberg equilibrium (SSE) is the standard solution concept of Stackelberg security games. As opposed to the weak Stackelberg equilibrium (WSE), the SSE assumes that the…
Deep Reinforcement Learning for Green Security Games with Real-Time Information
Yufei Wang, Zheyuan Ryan Shi, Lantao Yu +4
Green Security Games (GSGs) have been proposed and applied to optimize patrols conducted by law enforcement agencies in green security domains such as combating poaching, illegal l…
What game are we playing? End-to-end learning in normal and extensive form games
Chun Kai Ling, Fei Fang, J. Zico Kolter
Although recent work in AI has made great progress in solving large, zero-sum, extensive-form games, the underlying assumption in most past work is that the parameters of the game…
Designing the Game to Play: Optimizing Payoff Structure in Security Games
Zheyuan Ryan Shi, Ziye Tang, Long Tran-Thanh +2
Effective game-theoretic modeling of defender-attacker behavior is becoming increasingly important. In many domains, the defender functions not only as a player but also the design…