16.2k citations · 16.2k across the 3 of their papers we have counts for
6 papers
Improving Policies via Search in Cooperative Partially Observable Games
Adam Lerer, Hengyuan Hu, Jakob Foerster +1
Recent superhuman results in games have largely been achieved in a variety of zero-sum settings, such as Go and Poker, in which agents need to compete against others. However, just…
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa +18
Deep learning frameworks have often focused on either usability or speed, but not both. PyTorch is a machine learning library that shows that these two goals are in fact compatible…
PyTorch-BigGraph: A Large-scale Graph Embedding System
Adam Lerer, Ledell Wu, Jiajun Shen +4
Graph embedding methods produce unsupervised node features from graphs that can then be used for a variety of machine learning tasks. Modern graphs, particularly in industrial appl…
Robust Multi-agent Counterfactual Prediction
Alexander Peysakhovich, Christian Kroer, Adam Lerer
We consider the problem of using logged data to make predictions about what would happen if we changed the `rules of the game' in a multi-agent system. This task is difficult becau…
Prosocial learning agents solve generalized Stag Hunts better than selfish ones
Alexander Peysakhovich, Adam Lerer
Deep reinforcement learning has become an important paradigm for constructing agents that can enter complex multi-agent situations and improve their policies through experience. On…
Learning Physical Intuition of Block Towers by Example
Adam Lerer, Sam Gross, Rob Fergus
Wooden blocks are a common toy for infants, allowing them to develop motor skills and gain intuition about the physical behavior of the world. In this paper, we explore the ability…