research
∙
12/22/2022
Impossibility Theorems for Feature Attribution
Despite a sea of interpretability methods that can produce plausible exp...
share
research
∙
11/29/2022
Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration
Microprocessor architects are increasingly resorting to domain-specific ...
research
∙
08/09/2022
Basis for Intentions: Efficient Inverse Reinforcement Learning using Past Experience
This paper addresses the problem of inverse reinforcement learning (IRL)...
research
∙
01/21/2022
Environment Generation for Zero-Shot Compositional Reinforcement Learning
Many real-world problems are compositional - solving them requires compl...
research
∙
11/25/2021
Less is More: Generating Grounded Navigation Instructions from Landmarks
We study the automatic generation of navigation instructions from 360-de...
research
∙
07/12/2021
Explore and Control with Adversarial Surprise
Reinforcement learning (RL) provides a framework for learning goal-direc...
research
∙
04/15/2021
Joint Attention for Multi-Agent Coordination and Social Learning
Joint attention - the ability to purposefully coordinate attention with ...
research
∙
03/02/2021
Adversarial Environment Generation for Learning to Navigate the Web
Learning to autonomously navigate the web is a difficult sequential deci...
research
∙
02/24/2021
PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning
We study reinforcement learning (RL) with no-reward demonstrations, a se...
research
∙
12/03/2020
Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design
A wide range of reinforcement learning (RL) problems - including robustn...
research
∙
10/12/2020
Human-centric Dialog Training via Offline Reinforcement Learning
How can we train a dialog model to produce better conversations by learn...
research
∙
10/01/2020
Learning Social Learning
Social learning is a key component of human and animal intelligence. By ...
research
∙
09/17/2019
Hierarchical Reinforcement Learning for Open-Domain Dialog
Open-domain dialog generation is a challenging problem; maximum likeliho...
research
∙
06/30/2019
Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog
Most deep reinforcement learning (RL) systems are not able to learn effe...
research
∙
06/21/2019
Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems
Building an open-domain conversational agent is a challenging problem. C...
research
∙
06/10/2019
Tackling Climate Change with Machine Learning
Climate change is one of the greatest challenges facing humanity, and we...
research
∙
10/19/2018
Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning
We propose a unified mechanism for achieving coordination and communicat...
research
∙
10/19/2018
Intrinsic Social Motivation via Causal Influence in Multi-Agent RL
We derive a new intrinsic social motivation for multi-agent reinforcemen...
research
∙
02/13/2018
Learning via social awareness: improving sketch representations with facial feedback
In the quest towards general artificial intelligence (AI), researchers h...
research
∙
11/09/2016