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Decision Transformer: Reinforcement Learning via Sequence Modeling
Lili Chen*,
Kevin Lu*,
Aravind Rajeswaran,
Kimin Lee,
Aditya Grover,
Michael Laskin,
Pieter Abbeel,
Aravind Srinivas*,
Igor Mordatch*
Neural Information Processing Systems (NeurIPS), 2021
Official:
arXiv /
website /
poster /
tweet /
code
Press:
The Batch article /
SyncedReview article /
The Gradient article /
Yannic Kilcher video /
Eindhoven RL seminar
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Pretrained Transformers as Universal Computation Engines
Kevin Lu,
Aditya Grover,
Pieter Abbeel,
Igor Mordatch
AAAI Conference on Artificial Intelligence, 2022
Official:
arXiv /
blog /
poster /
tweet /
code
Press:
The Batch article /
VentureBeat article /
TWIML podcast /
Yannic Kilcher video
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Pretraining for Language-Conditioned Imitation with Transformers
Aaron (Louie) Putterman,
Kevin Lu,
Igor Mordatch,
Pieter Abbeel
NeurIPS Offline Reinforcement Learning Workshop, 2021
Official:
paper /
code
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URLB: Unsupervised Reinforcement Learning Benchmark
Michael Laskin*,
Denis Yarats*,
Hao Liu,
Kimin Lee,
Albert Zhan,
Kevin Lu,
Catherine Cang,
Lerrel Pinto,
Pieter Abbeel
Neural Information Processing Systems (NeurIPS), 2021
Official:
arXiv /
blog /
tweet /
code
Press:
Import AI article
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Reset-Free Lifelong Learning with Skill-Space Planning
Kevin Lu,
Aditya Grover,
Pieter Abbeel,
Igor Mordatch
International Conference on Learning Representations (ICLR), 2021
Official:
arXiv /
website /
oral /
poster /
tweet /
code
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Efficient Empowerment Estimation for Unsupervised Stabilization
Ruihan Zhao,
Kevin Lu,
Pieter Abbeel,
Stas Tiomkin
International Conference on Learning Representations (ICLR), 2021
Official:
arXiv /
website /
code
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Adaptive Online Planning for Continual Lifelong Learning
Kevin Lu,
Igor Mordatch,
Pieter Abbeel
NeurIPS Deep Reinforcement Learning Workshop, 2019
Official:
arXiv /
website /
oral /
poster /
code
Press:
Alignment Newsletter article
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