665 citations · 2.3k across the 48 of their papers we have counts for
4 papers · 1 filter
Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks
Amanpreet Singh, Tushar Jain, Sainbayar Sukhbaatar
Learning when to communicate and doing that effectively is essential in multi-agent tasks. Recent works show that continuous communication allows efficient training with back-propa…
Learning Goal Embeddings via Self-Play for Hierarchical Reinforcement Learning
Sainbayar Sukhbaatar, Emily Denton, Arthur Szlam +1
In hierarchical reinforcement learning a major challenge is determining appropriate low-level policies. We propose an unsupervised learning scheme, based on asymmetric self-play fr…
Planning with Arithmetic and Geometric Attributes
David Folqué, Sainbayar Sukhbaatar, Arthur Szlam +1
A desirable property of an intelligent agent is its ability to understand its environment to quickly generalize to novel tasks and compose simpler tasks into more complex ones. If…
Composable Planning with Attributes
Amy Zhang, Adam Lerer, Sainbayar Sukhbaatar +2
The tasks that an agent will need to solve often are not known during training. However, if the agent knows which properties of the environment are important then, after learning h…