58 citations · 72 across the 2 of their papers we have counts for
6 papers
Joint Policy Search for Multi-agent Collaboration with Imperfect Information
Yuandong Tian, Qucheng Gong, Tina Jiang
To learn good joint policies for multi-agent collaboration with imperfect information remains a fundamental challenge. While for two-player zero-sum games, coordinate-ascent approa…
Combining Deep Reinforcement Learning and Search for Imperfect-Information Games
Noam Brown, Anton Bakhtin, Adam Lerer +1
The combination of deep reinforcement learning and search at both training and test time is a powerful paradigm that has led to a number of successes in single-agent settings and p…
Polygames: Improved Zero Learning
Tristan Cazenave, Yen-Chi Chen, Guan-Wei Chen +21
Since DeepMind's AlphaZero, Zero learning quickly became the state-of-the-art method for many board games. It can be improved using a fully convolutional structure (no fully connec…
Luck Matters: Understanding Training Dynamics of Deep ReLU Networks
Yuandong Tian, Tina Jiang, Qucheng Gong +1
We analyze the dynamics of training deep ReLU networks and their implications on generalization capability. Using a teacher-student setting, we discovered a novel relationship betw…
Hierarchical Decision Making by Generating and Following Natural Language Instructions
Hengyuan Hu, Denis Yarats, Qucheng Gong +2
We explore using latent natural language instructions as an expressive and compositional representation of complex actions for hierarchical decision making. Rather than directly se…
ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games
Yuandong Tian, Qucheng Gong, Wenling Shang +2
In this paper, we propose ELF, an Extensive, Lightweight and Flexible platform for fundamental reinforcement learning research. Using ELF, we implement a highly customizable real-t…