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Information-Directed Exploration for Deep Reinforcement Learning
18 December 2018
Nikolay Nikolov
Johannes Kirschner
Felix Berkenkamp
Andreas Krause
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Papers citing
"Information-Directed Exploration for Deep Reinforcement Learning"
50 / 54 papers shown
Value of Information-Enhanced Exploration in Bootstrapped DQN
IEEE International Joint Conference on Neural Network (IJCNN), 2025
Stergios Plataniotis
Charilaos Akasiadis
Georgios Chalkiadakis
146
0
0
04 Nov 2025
Pretraining in Actor-Critic Reinforcement Learning for Robot Locomotion
Jiale Fan
Andrei Cramariuc
Tifanny Portela
Marco Hutter
123
0
0
14 Oct 2025
Uncertainty-driven Adaptive Exploration
Leonidas Bakopoulos
Georgios Chalkiadakis
190
0
0
03 Sep 2025
Uncertainty Prioritized Experience Replay
Rodrigo Carrasco-Davis
Sebastian Lee
Claudia Clopath
Will Dabney
225
1
0
10 Jun 2025
Universal Value-Function Uncertainties
Moritz A. Zanger
Max Weltevrede
Yaniv Oren
Pascal R. van der Vaart
Caroline Horsch
Wendelin Bohmer
M. Spaan
OffRL
289
0
0
27 May 2025
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model
Moritz A. Zanger
Pascal R. van der Vaart
Wendelin Bohmer
M. Spaan
UQCV
BDL
1.0K
4
0
14 Mar 2025
Learning to Assist Humans without Inferring Rewards
Neural Information Processing Systems (NeurIPS), 2024
Vivek Myers
Evan Ellis
Sergey Levine
Benjamin Eysenbach
Anca Dragan
577
10
0
17 Jan 2025
Directed Exploration in Reinforcement Learning from Linear Temporal Logic
Marco Bagatella
Andreas Krause
Georg Martius
OffRL
315
4
0
18 Aug 2024
Model-Free Active Exploration in Reinforcement Learning
Alessio Russo
Alexandre Proutiere
OffRL
254
5
0
30 Jun 2024
Reinforcement Learning with Intrinsically Motivated Feedback Graph for Lost-sales Inventory Control
Zifan Liu
Xinran Li
Shibo Chen
Gen Li
Jiashuo Jiang
Jun Zhang
243
0
0
26 Jun 2024
Pessimistic Value Iteration for Multi-Task Data Sharing in Offline Reinforcement Learning
Chenjia Bai
Lingxiao Wang
Jianye Hao
Zhuoran Yang
Bin Zhao
Zhen Wang
Xuelong Li
OffRL
272
10
0
30 Apr 2024
Provably Efficient Information-Directed Sampling Algorithms for Multi-Agent Reinforcement Learning
Qiaosheng Zhang
Chenjia Bai
Shuyue Hu
Zhen Wang
Xuelong Li
295
2
0
30 Apr 2024
A unified uncertainty-aware exploration: Combining epistemic and aleatory uncertainty
Parvin Malekzadeh
Ming Hou
Konstantinos N. Plataniotis
UD
213
5
0
05 Jan 2024
OVD-Explorer: Optimism Should Not Be the Sole Pursuit of Exploration in Noisy Environments
Jinyi Liu
Zhi Wang
Yan Zheng
Jianye Hao
Chenjia Bai
Junjie Ye
Zhen Wang
Haiyin Piao
Yang Sun
304
13
0
19 Dec 2023
Thompson sampling for improved exploration in GFlowNets
Jarrid Rector-Brooks
Kanika Madan
Moksh Jain
Maksym Korablyov
Cheng-Hao Liu
Sarath Chandar
Nikolay Malkin
Yoshua Bengio
208
32
0
30 Jun 2023
Diverse Projection Ensembles for Distributional Reinforcement Learning
International Conference on Learning Representations (ICLR), 2023
Moritz A. Zanger
Wendelin Bohmer
M. Spaan
247
7
0
12 Jun 2023
Seizing Serendipity: Exploiting the Value of Past Success in Off-Policy Actor-Critic
International Conference on Machine Learning (ICML), 2023
Tianying Ji
Yuping Luo
Gang Hua
Xianyuan Zhan
Jianwei Zhang
Huazhe Xu
OffRL
OnRL
408
21
0
05 Jun 2023
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning
Journal of machine learning research (JMLR), 2023
Wei-Fang Sun
Cheng-Kuang Lee
Simon See
Chun-Yi Lee
OffRL
230
3
0
04 Jun 2023
ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages
International Conference on Machine Learning (ICML), 2023
Andrew Jesson
Chris Xiaoxuan Lu
Gunshi Gupta
Angelos Filos
Jakob N. Foerster
Y. Gal
OffRL
361
9
0
02 Jun 2023
Latent Exploration for Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2023
A. Chiappa
Alessandro Marin Vargas
Ann Zixiang Huang
Alexander Mathis
321
27
0
31 May 2023
Exploration via Epistemic Value Estimation
AAAI Conference on Artificial Intelligence (AAAI), 2023
Simon Schmitt
John Shawe-Taylor
Hado van Hasselt
OffRL
166
4
0
07 Mar 2023
Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning
Adaptive Agents and Multi-Agent Systems (AAMAS), 2023
Ji-Yun Oh
Joonkee Kim
Minchan Jeong
Se-Young Yun
194
3
0
03 Mar 2023
Linear Partial Monitoring for Sequential Decision-Making: Algorithms, Regret Bounds and Applications
Journal of machine learning research (JMLR), 2023
Johannes Kirschner
Tor Lattimore
Andreas Krause
274
10
0
07 Feb 2023
MEET: A Monte Carlo Exploration-Exploitation Trade-off for Buffer Sampling
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022
Julius Ott
Lorenzo Servadei
Jose A. Arjona-Medina
E. Rinaldi
Gianfranco Mauro
Daniela Sanchez Lopera
Michael Stephan
Thomas Stadelmayer
Avik Santra
Robert Wille
194
0
0
24 Oct 2022
Exploration via Planning for Information about the Optimal Trajectory
Neural Information Processing Systems (NeurIPS), 2022
Viraj Mehta
I. Char
J. Abbate
R. Conlin
M. Boyer
Stefano Ermon
J. Schneider
Willie Neiswanger
OffRL
203
7
0
06 Oct 2022
Some Supervision Required: Incorporating Oracle Policies in Reinforcement Learning via Epistemic Uncertainty Metrics
Jun Jet Tai
Jordan Terry
M. Innocente
J. Brusey
N. Horri
277
3
0
22 Aug 2022
Distributional Actor-Critic Ensemble for Uncertainty-Aware Continuous Control
IEEE International Joint Conference on Neural Network (IJCNN), 2022
T. Kanazawa
Haiyan Wang
Chetan Gupta
UQCV
282
7
0
27 Jul 2022
Regret Bounds for Information-Directed Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2022
Botao Hao
Tor Lattimore
OffRL
268
23
0
09 Jun 2022
Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning
Bertrand Charpentier
Ransalu Senanayake
Mykel Kochenderfer
Stephan Günnemann
PER
UD
209
31
0
03 Jun 2022
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses
International Conference on Machine Learning (ICML), 2022
D. Tiapkin
Denis Belomestny
Eric Moulines
A. Naumov
S. Samsonov
Yunhao Tang
Michal Valko
Pierre Menard
237
21
0
16 May 2022
Non-Stationary Bandit Learning via Predictive Sampling
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Yueyang Liu
Kuang Xu
Benjamin Van Roy
445
21
0
04 May 2022
Exploration in Deep Reinforcement Learning: A Survey
Information Fusion (Inf. Fusion), 2022
Pawel Ladosz
Lilian Weng
Minwoo Kim
H. Oh
OffRL
314
496
0
02 May 2022
Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning
International Conference on Learning Representations (ICLR), 2022
Chenjia Bai
Lingxiao Wang
Zhuoran Yang
Zhihong Deng
Animesh Garg
Peng Liu
Zhaoran Wang
OffRL
284
157
0
23 Feb 2022
Occupancy Information Ratio: Infinite-Horizon, Information-Directed, Parameterized Policy Search
Wesley A Suttle
Alec Koppel
Ji Liu
196
0
0
21 Jan 2022
Gaussian Imagination in Bandit Learning
Yueyang Liu
Adithya M. Devraj
Benjamin Van Roy
Kuang Xu
218
7
0
06 Jan 2022
An Experimental Design Perspective on Model-Based Reinforcement Learning
Viraj Mehta
Biswajit Paria
J. Schneider
Stefano Ermon
Willie Neiswanger
OffRL
206
23
0
09 Dec 2021
The Value of Information When Deciding What to Learn
Dilip Arumugam
Benjamin Van Roy
171
16
0
26 Oct 2021
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain
Jianye Hao
Zhenxing Ge
Hongyao Tang
Chenjia Bai
Jinyi Liu
Zhaopeng Meng
Peng Liu
Zhen Wang
OffRL
377
158
0
14 Sep 2021
Disentangling What and Where for 3D Object-Centric Representations Through Active Inference
Toon Van de Maele
Tim Verbelen
Ozan Çatal
Bart Dhoedt
OCL
161
5
0
26 Aug 2021
GMAC: A Distributional Perspective on Actor-Critic Framework
International Conference on Machine Learning (ICML), 2021
D. W. Nam
Younghoon Kim
Chan Y. Park
240
21
0
24 May 2021
Principled Exploration via Optimistic Bootstrapping and Backward Induction
International Conference on Machine Learning (ICML), 2021
Chenjia Bai
Lingxiao Wang
Lei Han
Jianye Hao
Animesh Garg
Peng Liu
Zhaoran Wang
OffRL
196
45
0
13 May 2021
Reinforcement Learning, Bit by Bit
Xiuyuan Lu
Benjamin Van Roy
Vikranth Dwaracherla
M. Ibrahimi
Ian Osband
Zheng Wen
570
77
0
06 Mar 2021
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
International Conference on Machine Learning (ICML), 2021
Wei-Fang Sun
Cheng-Kuang Lee
Chun-Yi Lee
OffRL
222
52
0
16 Feb 2021
Measuring Progress in Deep Reinforcement Learning Sample Efficiency
Florian E. Dorner
138
13
0
09 Feb 2021
Leveraging the Variance of Return Sequences for Exploration Policy
Zerong Xi
G. Sukthankar
148
0
0
17 Nov 2020
Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning
Guangxiang Zhu
Minghao Zhang
Honglak Lee
Chongjie Zhang
OffRL
307
21
0
23 Oct 2020
On the Sample Complexity of Reinforcement Learning with Policy Space Generalization
Wenlong Mou
Zheng Wen
Xi Chen
184
12
0
17 Aug 2020
Hypermodels for Exploration
International Conference on Learning Representations (ICLR), 2020
Vikranth Dwaracherla
Xiuyuan Lu
M. Ibrahimi
Ian Osband
Zheng Wen
Benjamin Van Roy
BDL
192
47
0
12 Jun 2020
Segregation Dynamics with Reinforcement Learning and Agent Based Modeling
Scientific Reports (Sci Rep), 2019
Egemen Sert
Y. Bar-Yam
A. Morales
148
48
0
18 Sep 2019
Dueling Posterior Sampling for Preference-Based Reinforcement Learning
Conference on Uncertainty in Artificial Intelligence (UAI), 2019
Ellen R. Novoseller
Yibing Wei
Yanan Sui
Yisong Yue
J. W. Burdick
401
70
0
04 Aug 2019
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