5.6k citations · 16.3k across the 53 of their papers we have counts for
5 papers · 1 filter
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…
Modeling Others using Oneself in Multi-Agent Reinforcement Learning
Roberta Raileanu, Emily Denton, Arthur Szlam +1
We consider the multi-agent reinforcement learning setting with imperfect information in which each agent is trying to maximize its own utility. The reward function depends on the…
Stochastic Video Generation with a Learned Prior
Remi Denton, Rob Fergus
Generating video frames that accurately predict future world states is challenging. Existing approaches either fail to capture the full distribution of outcomes, or yield blurry ge…
IntPhys: A Framework and Benchmark for Visual Intuitive Physics Reasoning
Ronan Riochet, Mario Ynocente Castro, Mathieu Bernard +4
In order to reach human performance on complexvisual tasks, artificial systems need to incorporate a sig-nificant amount of understanding of the world in termsof macroscopic object…
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…