68 citations · 226 across the 24 of their papers we have counts for
7 papers · 1 filter
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.…
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…
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…
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…
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…