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All You Need Is Supervised Learning: From Imitation Learning to Meta-RL
  With Upside Down RL

All You Need Is Supervised Learning: From Imitation Learning to Meta-RL With Upside Down RL

24 February 2022
Kai Arulkumaran
Dylan R. Ashley
Jürgen Schmidhuber
R. Srivastava
    OffRL
ArXiv (abs)PDFHTML

Papers citing "All You Need Is Supervised Learning: From Imitation Learning to Meta-RL With Upside Down RL"

13 / 13 papers shown
Title
Pessimism Principle Can Be Effective: Towards a Framework for Zero-Shot Transfer Reinforcement Learning
Pessimism Principle Can Be Effective: Towards a Framework for Zero-Shot Transfer Reinforcement Learning
Chi Zhang
Ziying Jia
George Atia
Sihong He
Yue Wang
95
0
0
24 May 2025
RvS: What is Essential for Offline RL via Supervised Learning?
RvS: What is Essential for Offline RL via Supervised Learning?
Scott Emmons
Benjamin Eysenbach
Ilya Kostrikov
Sergey Levine
OffRL
71
183
0
20 Dec 2021
Generalized Decision Transformer for Offline Hindsight Information
  Matching
Generalized Decision Transformer for Offline Hindsight Information Matching
Hiroki Furuta
Y. Matsuo
S. Gu
OffRL
60
103
0
19 Nov 2021
Perceiver IO: A General Architecture for Structured Inputs & Outputs
Perceiver IO: A General Architecture for Structured Inputs & Outputs
Andrew Jaegle
Sebastian Borgeaud
Jean-Baptiste Alayrac
Carl Doersch
Catalin Ionescu
...
Olivier J. Hénaff
M. Botvinick
Andrew Zisserman
Oriol Vinyals
João Carreira
MLLMVLMGNN
76
583
0
30 Jul 2021
Offline Reinforcement Learning as One Big Sequence Modeling Problem
Offline Reinforcement Learning as One Big Sequence Modeling Problem
Michael Janner
Qiyang Li
Sergey Levine
OffRL
142
684
0
03 Jun 2021
Transient Non-Stationarity and Generalisation in Deep Reinforcement
  Learning
Transient Non-Stationarity and Generalisation in Deep Reinforcement Learning
Maximilian Igl
Gregory Farquhar
Jelena Luketina
Wendelin Boehmer
Shimon Whiteson
75
88
0
10 Jun 2020
Reward-Conditioned Policies
Reward-Conditioned Policies
Aviral Kumar
Xue Bin Peng
Sergey Levine
65
96
0
31 Dec 2019
Training Agents using Upside-Down Reinforcement Learning
Training Agents using Upside-Down Reinforcement Learning
R. Srivastava
Pranav Shyam
Filipe Wall Mutz
Wojciech Ja'skowski
Jürgen Schmidhuber
OffRL
70
126
0
05 Dec 2019
Reinforcement Learning Upside Down: Don't Predict Rewards -- Just Map
  Them to Actions
Reinforcement Learning Upside Down: Don't Predict Rewards -- Just Map Them to Actions
J. Schmidhuber
65
131
0
05 Dec 2019
Language as an Abstraction for Hierarchical Deep Reinforcement Learning
Language as an Abstraction for Hierarchical Deep Reinforcement Learning
Yiding Jiang
S. Gu
Kevin Patrick Murphy
Chelsea Finn
OffRL
55
225
0
18 Jun 2019
Learning to Generalize: Meta-Learning for Domain Generalization
Learning to Generalize: Meta-Learning for Domain Generalization
Da Li
Yongxin Yang
Yi-Zhe Song
Timothy M. Hospedales
OOD
102
1,421
0
10 Oct 2017
Learning to reinforcement learn
Learning to reinforcement learn
Jane X. Wang
Z. Kurth-Nelson
Dhruva Tirumala
Hubert Soyer
Joel Z Leibo
Rémi Munos
Charles Blundell
D. Kumaran
M. Botvinick
OffRL
97
980
0
17 Nov 2016
RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning
RL2^22: Fast Reinforcement Learning via Slow Reinforcement Learning
Yan Duan
John Schulman
Xi Chen
Peter L. Bartlett
Ilya Sutskever
Pieter Abbeel
OffRL
99
1,019
0
09 Nov 2016
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