activity
20172021
most citedExploring the acceleration of Nekbone on reconfigurable architectures

19 citations · 45 across the 6 of their papers we have counts for

collaborators

15 papers

cs.LG2021

No-Press Diplomacy from Scratch

Anton Bakhtin, David Wu, Adam Lerer +1

Prior AI successes in complex games have largely focused on settings with at most hundreds of actions at each decision point. In contrast, Diplomacy is a game with more than 10^20…

cs.AI20216 cited

Scalable Online Planning via Reinforcement Learning Fine-Tuning

Arnaud Fickinger, Hengyuan Hu, Brandon Amos +2

Lookahead search has been a critical component of recent AI successes, such as in the games of chess, go, and poker. However, the search methods used in these games, and in many ot…

cs.AI20212 cited

Learned Belief Search: Efficiently Improving Policies in Partially Observable Settings

Hengyuan Hu, Adam Lerer, Noam Brown +1

Search is an important tool for computing effective policies in single- and multi-agent environments, and has been crucial for achieving superhuman performance in several benchmark…

cs.AI2021

Off-Belief Learning

Hengyuan Hu, Adam Lerer, Brandon Cui +4

The standard problem setting in Dec-POMDPs is self-play, where the goal is to find a set of policies that play optimally together. Policies learned through self-play may adopt arbi…

cs.GT2021

Safe Search for Stackelberg Equilibria in Extensive-Form Games

Chun Kai Ling, Noam Brown

Stackelberg equilibrium is a solution concept in two-player games where the leader has commitment rights over the follower. In recent years, it has become a cornerstone of many sec…

cs.DC202019 cited

Exploring the acceleration of Nekbone on reconfigurable architectures

Nick Brown

Hardware technological advances are struggling to match scientific ambition, and a key question is how we can use the transistors that we already have more effectively. This is esp…