21 citations · 21 across the 5 of their papers we have counts for
5 papers
A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
Haozhe Jiang, Qiwen Cui, Zhihan Xiong +2
We investigate learning the equilibria in non-stationary multi-agent systems and address the challenges that differentiate multi-agent learning from single-agent learning. Specific…
Offline Meta Reinforcement Learning with In-Distribution Online Adaptation
Jianhao Wang, Jin Zhang, Haozhe Jiang +3
Recent offline meta-reinforcement learning (meta-RL) methods typically utilize task-dependent behavior policies (e.g., training RL agents on each individual task) to collect a mult…
Practically Solving LPN in High Noise Regimes Faster Using Neural Networks
Haozhe Jiang, Kaiyue Wen, Yilei Chen
We conduct a systematic study of solving the learning parity with noise problem (LPN) using neural networks. Our main contribution is designing families of two-layer neural network…
Offline congestion games: How feedback type affects data coverage requirement
Haozhe Jiang, Qiwen Cui, Zhihan Xiong +2
This paper investigates when one can efficiently recover an approximate Nash Equilibrium (NE) in offline congestion games. The existing dataset coverage assumption in offline gener…
Offline Reinforcement Learning with Reverse Model-based Imagination
Jianhao Wang, Wenzhe Li, Haozhe Jiang +3
In offline reinforcement learning (offline RL), one of the main challenges is to deal with the distributional shift between the learning policy and the given dataset. To address th…