Aravind Rajeswaran

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Visual Adversarial Imitation Learning using Variational Models

Reward function specification, which requires considerable human effort ...
07/16/2021 ∙ by Rafael Rafailov, et al. ∙ 6 ∙ share

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Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL

Offline Reinforcement Learning (RL) aims to extract near-optimal policie...
06/16/2021 ∙ by Catherine Cang, et al. ∙ 0 ∙ share

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Decision Transformer: Reinforcement Learning via Sequence Modeling

We present a framework that abstracts Reinforcement Learning (RL) as a s...
06/02/2021 ∙ by Lili Chen, et al. ∙ 0 ∙ share

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COMBO: Conservative Offline Model-Based Policy Optimization

Model-based algorithms, which learn a dynamics model from logged experie...
02/16/2021 ∙ by Tianhe Yu, et al. ∙ 0 ∙ share

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Offline Reinforcement Learning from Images with Latent Space Models

Offline reinforcement learning (RL) refers to the problem of learning po...
12/21/2020 ∙ by Rafael Rafailov, et al. ∙ 10 ∙ share

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MOReL : Model-Based Offline Reinforcement Learning

In offline reinforcement learning (RL), the goal is to learn a successfu...
05/12/2020 ∙ by Rahul Kidambi, et al. ∙ 9 ∙ share

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A Game Theoretic Framework for Model Based Reinforcement Learning

Model-based reinforcement learning (MBRL) has recently gained immense in...
04/16/2020 ∙ by Aravind Rajeswaran, et al. ∙ 38 ∙ share

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Lyceum: An efficient and scalable ecosystem for robot learning

We introduce Lyceum, a high-performance computational ecosystem for robo...
01/21/2020 ∙ by Colin Summers, et al. ∙ 9 ∙ share

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Meta-Learning with Implicit Gradients

A core capability of intelligent systems is the ability to quickly learn...
09/10/2019 ∙ by Aravind Rajeswaran, et al. ∙ 2 ∙ share

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Online Meta-Learning

A central capability of intelligent systems is the ability to continuous...
02/22/2019 ∙ by Chelsea Finn, et al. ∙ 54 ∙ share

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Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control

We propose a plan online and learn offline (POLO) framework for the sett...
11/05/2018 ∙ by Kendall Lowrey, et al. ∙ 4 ∙ share

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Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost

Dexterous multi-fingered robotic hands can perform a wide range of manip...
10/14/2018 ∙ by Henry Zhu, et al. ∙ 0 ∙ share

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Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system

Reinforcement learning has emerged as a promising methodology for traini...
03/28/2018 ∙ by Kendall Lowrey, et al. ∙ 0 ∙ share

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Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines

Policy gradient methods have enjoyed great success in deep reinforcement...
03/20/2018 ∙ by Cathy Wu, et al. ∙ 0 ∙ share

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Divide-and-Conquer Reinforcement Learning

Standard model-free deep reinforcement learning (RL) algorithms sample a...
11/27/2017 ∙ by Dibya Ghosh, et al. ∙ 0 ∙ share

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Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations

Dexterous multi-fingered hands are extremely versatile and provide a gen...
09/28/2017 ∙ by Aravind Rajeswaran, et al. ∙ 0 ∙ share

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EPOpt: Learning Robust Neural Network Policies Using Model Ensembles

Sample complexity and safety are major challenges when learning policies...
10/05/2016 ∙ by Aravind Rajeswaran, et al. ∙ 0 ∙ share

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A Novel Approach for Phase Identification in Smart Grids Using Graph Theory and Principal Component Analysis

Consumers with low demand, like households, are generally supplied singl...
11/19/2015 ∙ by P Satya Jayadev, et al. ∙ 0 ∙ share

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Aravind Rajeswaran

Featured Co-authors

Sergey Levine

Pieter Abbeel

Chelsea Finn

Abhishek Gupta

Balaraman Ravindran

Praneeth Netrapalli

Sham Kakade

Igor Mordatch

Thorsten Joachims

Aditya Grover

Kimin Lee

Visual Adversarial Imitation Learning using Variational Models

Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL

Decision Transformer: Reinforcement Learning via Sequence Modeling

COMBO: Conservative Offline Model-Based Policy Optimization

Offline Reinforcement Learning from Images with Latent Space Models

MOReL : Model-Based Offline Reinforcement Learning

A Game Theoretic Framework for Model Based Reinforcement Learning

Lyceum: An efficient and scalable ecosystem for robot learning

Meta-Learning with Implicit Gradients

Online Meta-Learning

Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control

Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost

Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system

Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines

Divide-and-Conquer Reinforcement Learning

Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations

EPOpt: Learning Robust Neural Network Policies Using Model Ensembles

A Novel Approach for Phase Identification in Smart Grids Using Graph Theory and Principal Component Analysis