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One Big Net For Everything

One Big Net For Everything

24 February 2018
Jürgen Schmidhuber
    CLL
ArXiv (abs)PDFHTML

Papers citing "One Big Net For Everything"

16 / 16 papers shown
Title
Habits and goals in synergy: a variational Bayesian framework for
  behavior
Habits and goals in synergy: a variational Bayesian framework for behavior
Dongqi Han
Kenji Doya
Dongsheng Li
Jun Tani
BDL
78
215
0
11 Apr 2023
Guiding Online Reinforcement Learning with Action-Free Offline
  Pretraining
Guiding Online Reinforcement Learning with Action-Free Offline Pretraining
Deyao Zhu
Yuhui Wang
Jürgen Schmidhuber
Mohamed Elhoseiny
OffRLOnRL
83
8
0
30 Jan 2023
Learning One Abstract Bit at a Time Through Self-Invented Experiments
  Encoded as Neural Networks
Learning One Abstract Bit at a Time Through Self-Invented Experiments Encoded as Neural Networks
Vincent Herrmann
Louis Kirsch
Jürgen Schmidhuber
AI4CE
109
6
0
29 Dec 2022
On Realization of Intelligent Decision-Making in the Real World: A
  Foundation Decision Model Perspective
On Realization of Intelligent Decision-Making in the Real World: A Foundation Decision Model Perspective
Ying Wen
Bo Liu
M. Zhou
Shufang Hou
Zhe Cao
Chenyang Le
Jingxiao Chen
Zheng Tian
Weinan Zhang
Jun Wang
AI4CE
73
11
0
24 Dec 2022
A Generalist Agent
A Generalist Agent
Scott E. Reed
Konrad Zolna
Emilio Parisotto
Sergio Gomez Colmenarejo
Alexander Novikov
...
Yutian Chen
R. Hadsell
Oriol Vinyals
Mahyar Bordbar
Nando de Freitas
LM&RoLLMAGAI4CE
217
827
0
12 May 2022
On the link between conscious function and general intelligence in
  humans and machines
On the link between conscious function and general intelligence in humans and machines
Arthur Juliani
Kai Arulkumaran
Shuntaro Sasai
Ryota Kanai
105
26
0
24 Mar 2022
Deep Learning: Our Miraculous Year 1990-1991
Deep Learning: Our Miraculous Year 1990-1991
J. Schmidhuber
3DGSMedIm
46
6
0
12 May 2020
Will we ever have Conscious Machines?
Will we ever have Conscious Machines?
P. Krauss
Andreas Maier
77
30
0
31 Mar 2020
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
86
133
0
05 Dec 2019
Continual Learning with Adaptive Weights (CLAW)
Continual Learning with Adaptive Weights (CLAW)
T. Adel
Han Zhao
Richard Turner
CLL
76
73
0
21 Nov 2019
Recurrent Independent Mechanisms
Recurrent Independent Mechanisms
Anirudh Goyal
Alex Lamb
Jordan Hoffmann
Shagun Sodhani
Sergey Levine
Yoshua Bengio
Bernhard Schölkopf
150
338
0
24 Sep 2019
Generative Adversarial Networks are Special Cases of Artificial
  Curiosity (1990) and also Closely Related to Predictability Minimization
  (1991)
Generative Adversarial Networks are Special Cases of Artificial Curiosity (1990) and also Closely Related to Predictability Minimization (1991)
J. Schmidhuber
GANDRL
110
57
0
11 Jun 2019
Self-organization of action hierarchy and compositionality by
  reinforcement learning with recurrent neural networks
Self-organization of action hierarchy and compositionality by reinforcement learning with recurrent neural networks
Dongqi Han
Kenji Doya
Jun Tani
AI4CE
116
20
0
29 Jan 2019
Unity: A General Platform for Intelligent Agents
Unity: A General Platform for Intelligent Agents
Arthur Juliani
Vincent-Pierre Berges
Esh Vckay
Andrew Cohen
Jonathan Harper
...
Chris Goy
Yuan Gao
Hunter Henry
Marwan Mattar
Danny Lange
94
822
0
07 Sep 2018
Progress & Compress: A scalable framework for continual learning
Progress & Compress: A scalable framework for continual learning
Jonathan Richard Schwarz
Jelena Luketina
Wojciech M. Czarnecki
A. Grabska-Barwinska
Yee Whye Teh
Razvan Pascanu
R. Hadsell
CLL
161
889
0
16 May 2018
World Models
World Models
David R Ha
Jürgen Schmidhuber
SyDa
202
1,102
0
27 Mar 2018
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