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1103.5708
Cited By
Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments
29 March 2011
Yi Sun
Faustino J. Gomez
Jürgen Schmidhuber
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Papers citing
"Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments"
50 / 74 papers shown
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Pragmatic information of aesthetic appraisal
Cognitive Neurodynamics (CN), 2024
Peter beim Graben
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Satisficing Exploration for Deep Reinforcement Learning
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287
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Adaptive Teaching in Heterogeneous Agents: Balancing Surprise in Sparse Reward Scenarios
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Emma Clark
Kanghyun Ryu
Negar Mehr
190
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Efficient Exploration for LLMs
Vikranth Dwaracherla
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516
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01 Feb 2024
Active Inference as a Model of Agency
Lancelot Da Costa
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401
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23 Jan 2024
Resolving uncertainty on the fly: Modeling adaptive driving behavior as active inference
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Ran Wei
Anthony D. McDonald
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Matthew O'Kelly
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244
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10 Nov 2023
Generative Intrinsic Optimization: Intrinsic Control with Model Learning
Jianfei Ma
302
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0
12 Oct 2023
A Unified View on Solving Objective Mismatch in Model-Based Reinforcement Learning
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Nathan Lambert
Anthony D. McDonald
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Roberto Calandra
415
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Active Sensing with Predictive Coding and Uncertainty Minimization
A. Sharafeldin
N. Imam
Hannah Choi
399
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02 Jul 2023
Grid-SD2E: A General Grid-Feedback in a System for Cognitive Learning
Jingyi Feng
Chenming Zhang
328
1
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04 Apr 2023
Modern Bayesian Experimental Design
Statistical Science (Statist. Sci.), 2023
Tom Rainforth
Adam Foster
Desi R. Ivanova
Freddie Bickford-Smith
378
177
0
28 Feb 2023
Learning One Abstract Bit at a Time Through Self-Invented Experiments Encoded as Neural Networks
International Workshop on Affective Interactions (AI), 2022
Vincent Herrmann
Louis Kirsch
Jürgen Schmidhuber
AI4CE
305
7
0
29 Dec 2022
Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments
International Conference on Machine Learning (ICML), 2022
Daniel Jarrett
Corentin Tallec
Florent Altché
Thomas Mesnard
Rémi Munos
Michal Valko
310
6
0
18 Nov 2022
Exploring through Random Curiosity with General Value Functions
Neural Information Processing Systems (NeurIPS), 2022
Aditya A. Ramesh
Louis Kirsch
Sjoerd van Steenkiste
Jürgen Schmidhuber
301
13
0
18 Nov 2022
An information-theoretic perspective on intrinsic motivation in reinforcement learning: a survey
A. Aubret
L. Matignon
S. Hassas
314
57
0
19 Sep 2022
Modelling non-reinforced preferences using selective attention
Noor Sajid
P. Tigas
Zafeirios Fountas
Qinghai Guo
Alexey Zakharov
Lancelot Da Costa
180
1
0
25 Jul 2022
BYOL-Explore: Exploration by Bootstrapped Prediction
Neural Information Processing Systems (NeurIPS), 2022
Z. Guo
S. Thakoor
Miruna Pislar
Bernardo Avila-Pires
Florent Altché
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Yunhao Tang
Michal Valko
Rémi Munos
M. G. Azar
Bilal Piot
356
92
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16 Jun 2022
Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents
Alessandro Barp
Lancelot Da Costa
G. Francca
Karl J. Friston
Mark Girolami
Michael I. Jordan
G. Pavliotis
433
27
0
20 Mar 2022
Optimizing Sequential Experimental Design with Deep Reinforcement Learning
International Conference on Machine Learning (ICML), 2022
Tom Blau
Edwin V. Bonilla
Iadine Chadès
Amir Dezfouli
BDL
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501
62
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02 Feb 2022
Information is Power: Intrinsic Control via Information Capture
Nick Rhinehart
Jenny Wang
Glen Berseth
John D. Co-Reyes
Danijar Hafner
Chelsea Finn
Sergey Levine
273
12
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Discovering and Achieving Goals via World Models
Russell Mendonca
Oleh Rybkin
Kostas Daniilidis
Danijar Hafner
Deepak Pathak
380
163
0
18 Oct 2021
Active inference, Bayesian optimal design, and expected utility
Noor Sajid
Lancelot Da Costa
Thomas Parr
Karl J. Friston
254
19
0
21 Sep 2021
Bayesian brains and the Rényi divergence
Noor Sajid
Francesco Faccio
Lancelot Da Costa
Thomas Parr
Jürgen Schmidhuber
Karl J. Friston
364
13
0
12 Jul 2021
Applications of the Free Energy Principle to Machine Learning and Neuroscience
Beren Millidge
DRL
447
12
0
30 Jun 2021
Understanding the Origin of Information-Seeking Exploration in Probabilistic Objectives for Control
Beren Millidge
A. Seth
Christopher L. Buckley
774
13
0
11 Mar 2021
Is Pessimism Provably Efficient for Offline RL?
International Conference on Machine Learning (ICML), 2020
Ying Jin
Zhuoran Yang
Zhaoran Wang
OffRL
804
415
0
30 Dec 2020
Evaluating Agents without Rewards
Brendon Matusch Jimmy Ba
Jimmy Ba
Danijar Hafner
339
13
0
21 Dec 2020
Reward Maximisation through Discrete Active Inference
Lancelot Da Costa
Noor Sajid
Thomas Parr
Karl J. Friston
Ryan Smith
591
4
0
17 Sep 2020
Action and Perception as Divergence Minimization
Danijar Hafner
Pedro A. Ortega
Jimmy Ba
Thomas Parr
Karl J. Friston
N. Heess
343
60
0
03 Sep 2020
Explore and Explain: Self-supervised Navigation and Recounting
International Conference on Pattern Recognition (ICPR), 2020
Roberto Bigazzi
Federico Landi
Marcella Cornia
S. Cascianelli
Lorenzo Baraldi
Rita Cucchiara
EgoV
LM&Ro
212
20
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14 Jul 2020
Continual Learning: Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes
Timothée Lesort
CLL
421
25
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01 Jul 2020
Adaptive Procedural Task Generation for Hard-Exploration Problems
Kuan Fang
Yuke Zhu
Silvio Savarese
Li Fei-Fei
435
34
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01 Jul 2020
AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning
Yuening Li
Zhengzhang Chen
Daochen Zha
Kaixiong Zhou
Haifeng Jin
Haifeng Chen
Helen Zhou
244
19
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19 Jun 2020
NROWAN-DQN: A Stable Noisy Network with Noise Reduction and Online Weight Adjustment for Exploration
Shuai Han
Wenbo Zhou
Jing Liu
Shuai Lu
156
38
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19 Jun 2020
MetaCURE: Meta Reinforcement Learning with Empowerment-Driven Exploration
Jin Zhang
Jianhao Wang
Hao Hu
Tong Chen
Yingfeng Chen
Changjie Fan
Chongjie Zhang
OffRL
266
32
0
15 Jun 2020
Sophisticated Inference
Karl J. Friston
Lancelot Da Costa
Danijar Hafner
C. Hesp
Thomas Parr
278
118
0
07 Jun 2020
Planning to Explore via Self-Supervised World Models
Ramanan Sekar
Oleh Rybkin
Kostas Daniilidis
Pieter Abbeel
Danijar Hafner
Deepak Pathak
SSL
443
485
0
12 May 2020
Whence the Expected Free Energy?
Neural Computation (Neural Comput.), 2020
Beren Millidge
Alexander Tschantz
Christopher L. Buckley
583
82
0
17 Apr 2020
Reinforcement Learning through Active Inference
Alexander Tschantz
Beren Millidge
A. Seth
Christopher L. Buckley
AI4CE
369
96
0
28 Feb 2020
Ready Policy One: World Building Through Active Learning
International Conference on Machine Learning (ICML), 2020
Philip J. Ball
Jack Parker-Holder
Aldo Pacchiano
K. Choromanski
Stephen J. Roberts
OffRL
279
52
0
07 Feb 2020
An Exploration of Embodied Visual Exploration
International Journal of Computer Vision (IJCV), 2020
Santhosh Kumar Ramakrishnan
Dinesh Jayaraman
Kristen Grauman
LM&Ro
514
112
0
07 Jan 2020
SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments
Glen Berseth
Daniel Geng
Coline Devin
Nicholas Rhinehart
Chelsea Finn
Dinesh Jayaraman
Sergey Levine
412
22
0
11 Dec 2019
Scaling active inference
IEEE International Joint Conference on Neural Network (IJCNN), 2019
Alexander Tschantz
Manuel Baltieri
A. Seth
Christopher L. Buckley
BDL
AI4CE
296
75
0
24 Nov 2019
Implicit Generative Modeling for Efficient Exploration
International Conference on Machine Learning (ICML), 2019
Neale Ratzlaff
Qinxun Bai
Fuxin Li
Wenyuan Xu
459
15
0
19 Nov 2019
VASE: Variational Assorted Surprise Exploration for Reinforcement Learning
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2019
Haitao Xu
B. McCane
Lech Szymanski
VLM
108
4
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31 Oct 2019
Receding Horizon Curiosity
Conference on Robot Learning (CoRL), 2019
M. Schultheis
Boris Belousov
Hany Abdulsamad
Jan Peters
162
16
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08 Oct 2019
Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning
IEEE Symposium Series on Computational Intelligence (SSCI), 2019
Xudong Sun
J. Herbinger
BDL
419
9
0
25 Aug 2019
Continual Learning for Robotics: Definition, Framework, Learning Strategies, Opportunities and Challenges
Information Fusion (Inf. Fusion), 2019
Timothée Lesort
Vincenzo Lomonaco
Andrei Stoian
Davide Maltoni
David Filliat
Natalia Díaz Rodríguez
CLL
468
298
0
29 Jun 2019
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