Natasha Jaques | DeepAI

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∙ 12/22/2022

Impossibility Theorems for Feature Attribution

Despite a sea of interpretability methods that can produce plausible exp...

3 Blair Bilodeau, et al. ∙

∙ 11/29/2022

Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration

Microprocessor architects are increasingly resorting to domain-specific ...

21 Srivatsan Krishnan, et al. ∙

∙ 08/09/2022

Basis for Intentions: Efficient Inverse Reinforcement Learning using Past Experience

This paper addresses the problem of inverse reinforcement learning (IRL)...

29 Marwa Abdulhai, et al. ∙

∙ 01/21/2022

Environment Generation for Zero-Shot Compositional Reinforcement Learning

Many real-world problems are compositional - solving them requires compl...

2 Izzeddin Gür, et al. ∙

∙ 11/25/2021

Less is More: Generating Grounded Navigation Instructions from Landmarks

We study the automatic generation of navigation instructions from 360-de...

8 Su Wang, et al. ∙

∙ 07/12/2021

Explore and Control with Adversarial Surprise

Reinforcement learning (RL) provides a framework for learning goal-direc...

4 Arnaud Fickinger, et al. ∙

∙ 04/15/2021

Joint Attention for Multi-Agent Coordination and Social Learning

Joint attention - the ability to purposefully coordinate attention with ...

14 Dennis Lee, et al. ∙

∙ 03/02/2021

Adversarial Environment Generation for Learning to Navigate the Web

Learning to autonomously navigate the web is a difficult sequential deci...

14 Izzeddin Gür, et al. ∙

∙ 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...

16 Angelos Filos, et al. ∙

∙ 12/03/2020

Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design

A wide range of reinforcement learning (RL) problems - including robustn...

0 Michael Dennis, et al. ∙

∙ 10/12/2020

Human-centric Dialog Training via Offline Reinforcement Learning

How can we train a dialog model to produce better conversations by learn...

4 Natasha Jaques, et al. ∙

∙ 10/01/2020

Learning Social Learning

Social learning is a key component of human and animal intelligence. By ...

35 Kamal Ndousse, et al. ∙

∙ 09/17/2019

Hierarchical Reinforcement Learning for Open-Domain Dialog

Open-domain dialog generation is a challenging problem; maximum likeliho...

5 Abdelrhman Saleh, et al. ∙

∙ 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...

9 Natasha Jaques, et al. ∙

∙ 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...

3 Asma Ghandeharioun, et al. ∙

∙ 06/10/2019

Tackling Climate Change with Machine Learning

Climate change is one of the greatest challenges facing humanity, and we...

1 David Rolnick, et al. ∙

∙ 10/19/2018

Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning

We propose a unified mechanism for achieving coordination and communicat...

0 Natasha Jaques, et al. ∙

∙ 10/19/2018

Intrinsic Social Motivation via Causal Influence in Multi-Agent RL

We derive a new intrinsic social motivation for multi-agent reinforcemen...

0 Natasha Jaques, et al. ∙

∙ 02/13/2018

Learning via social awareness: improving sketch representations with facial feedback

In the quest towards general artificial intelligence (AI), researchers h...

0 Natasha Jaques, et al. ∙

∙ 11/09/2016

Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control

This paper proposes a general method for improving the structure and qua...

0 Natasha Jaques, et al. ∙

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