Arun Ahuja | DeepAI

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Featured Co-authors

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∙ 09/20/2023

Hierarchical reinforcement learning with natural language subgoals

Hierarchical reinforcement learning has been a compelling approach for a...

0 Arun Ahuja, et al. ∙

∙ 02/01/2023

Collaborating with language models for embodied reasoning

Reasoning in a complex and ambiguous environment is a key goal for Reinf...

0 Ishita Dasgupta, et al. ∙

∙ 01/29/2023

Distilling Internet-Scale Vision-Language Models into Embodied Agents

Instruction-following agents must ground language into their observation...

0 Theodore Sumers, et al. ∙

∙ 11/21/2022

Improving Multimodal Interactive Agents with Reinforcement Learning from Human Feedback

An important goal in artificial intelligence is to create agents that ca...

0 Josh Abramson, et al. ∙

∙ 10/31/2022

Learning to Navigate Wikipedia by Taking Random Walks

A fundamental ability of an intelligent web-based agent is seeking out a...

0 Manzil Zaheer, et al. ∙

∙ 05/26/2022

Evaluating Multimodal Interactive Agents

Creating agents that can interact naturally with humans is a common goal...

0 Josh Abramson, et al. ∙

∙ 12/07/2021

Creating Multimodal Interactive Agents with Imitation and Self-Supervised Learning

A common vision from science fiction is that robots will one day inhabit...

1 DeepMind Interactive Agents Team, et al. ∙

∙ 07/08/2021

Imitation by Predicting Observations

Imitation learning enables agents to reuse and adapt the hard-won expert...

0 Andrew Jaegle, et al. ∙

∙ 12/10/2020

Imitating Interactive Intelligence

A common vision from science fiction is that robots will one day inhabit...

0 Josh Abramson, et al. ∙

∙ 10/27/2020

Behavior Priors for Efficient Reinforcement Learning

As we deploy reinforcement learning agents to solve increasingly challen...

10 Dhruva Tirumala, et al. ∙

∙ 06/01/2020

Probing Emergent Semantics in Predictive Agents via Question Answering

Recent work has shown how predictive modeling can endow agents with rich...

18 Abhishek Das, et al. ∙

∙ 11/15/2019

Reusable neural skill embeddings for vision-guided whole body movement and object manipulation

Both in simulation settings and robotics, there is an ambition to produc...

11 Josh Merel, et al. ∙

∙ 09/26/2019

V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control

Some of the most successful applications of deep reinforcement learning ...

0 H. Francis Song, et al. ∙

∙ 03/18/2019

Exploiting Hierarchy for Learning and Transfer in KL-regularized RL

As reinforcement learning agents are tasked with solving more challengin...

20 Dhruva Tirumala, et al. ∙

∙ 11/28/2018

Neural probabilistic motor primitives for humanoid control

We focus on the problem of learning a single motor module that can flexi...

12 Josh Merel, et al. ∙

∙ 11/28/2018

Experience Replay for Continual Learning

Continual learning is the problem of learning new tasks or knowledge whi...

0 David Rolnick, et al. ∙

∙ 11/23/2018

Hierarchical visuomotor control of humanoids

We aim to build complex humanoid agents that integrate perception, motor...

0 Josh Merel, et al. ∙

∙ 10/15/2018

Optimizing Agent Behavior over Long Time Scales by Transporting Value

Humans spend a remarkable fraction of waking life engaged in acts of "me...

0 Chia-Chun Hung, et al. ∙

∙ 04/03/2018

Probing Physics Knowledge Using Tools from Developmental Psychology

In order to build agents with a rich understanding of their environment,...

0 Luis Piloto, et al. ∙

∙ 03/28/2018

Unsupervised Predictive Memory in a Goal-Directed Agent

Animals execute goal-directed behaviours despite the limited range and s...

0 Greg Wayne, et al. ∙

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