Deep Reinforcement Learning and the Deadly Triad

6 December 2018

Papers citing "Deep Reinforcement Learning and the Deadly Triad"

50 / 60 papers shown

Title
1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities Kevin Wang Ishaan Javali Michał Bortkiewicz Tomasz Trzciñski Benjamin Eysenbach SSL OffRL 77 1 0 19 Mar 2025
EvoRL: A GPU-accelerated Framework for Evolutionary Reinforcement Learning Bowen Zheng Ran Cheng Kay Chen Tan 49 0 0 25 Jan 2025
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Zhen Liu Tim Z. Xiao Weiyang Liu Yoshua Bengio Dinghuai Zhang 123 4 0 10 Dec 2024
DIAR: Diffusion-model-guided Implicit Q-learning with Adaptive Revaluation Jaehyun Park Yunho Kim Sejin Kim Byung-Jun Lee Sundong Kim OffRL 39 1 0 15 Oct 2024
Frequency and Generalisation of Periodic Activation Functions in Reinforcement Learning Augustine N. Mavor-Parker Matthew J. Sargent Caswell Barry Lewis D. Griffin Clare Lyle 52 2 0 09 Jul 2024
Simplifying Deep Temporal Difference Learning Matteo Gallici Mattie Fellows Benjamin Ellis B. Pou Ivan Masmitja Jakob Foerster Mario Martin OffRL 62 17 0 05 Jul 2024
Is Value Functions Estimation with Classification Plug-and-play for Offline Reinforcement Learning? Denis Tarasov Kirill Brilliantov Dmitrii Kharlapenko OffRL 41 2 0 10 Jun 2024
Multi-agent Reinforcement Learning: A Comprehensive Survey Dom Huh Prasant Mohapatra AI4CE 36 8 0 15 Dec 2023
Adaptive Ensemble Q-learning: Minimizing Estimation Bias via Error Feedback Hang Wang Sen Lin Junshan Zhang 26 19 0 20 Jun 2023
Diverse Projection Ensembles for Distributional Reinforcement Learning Moritz A. Zanger Wendelin Bohmer M. Spaan 38 4 0 12 Jun 2023
Distance Weighted Supervised Learning for Offline Interaction Data Joey Hejna Jensen Gao Dorsa Sadigh OffRL 38 13 0 26 Apr 2023
The Dormant Neuron Phenomenon in Deep Reinforcement Learning Ghada Sokar Rishabh Agarwal Pablo Samuel Castro Utku Evci CLL 53 90 0 24 Feb 2023
Learning to Optimize for Reinforcement Learning Qingfeng Lan Rupam Mahmood Shuicheng Yan Zhongwen Xu OffRL 36 6 0 03 Feb 2023
Distillation Policy Optimization Jianfei Ma OffRL 26 1 0 01 Feb 2023
SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning Maxwell Standen Junae Kim Claudia Szabo AAML 44 5 0 11 Jan 2023
A Survey on Transformers in Reinforcement Learning Wenzhe Li Hao Luo Zichuan Lin Chongjie Zhang Zongqing Lu Deheng Ye OffRL MU AI4CE 37 56 0 08 Jan 2023
Is Conditional Generative Modeling all you need for Decision-Making? Anurag Ajay Yilun Du Abhi Gupta J. Tenenbaum Tommi Jaakkola Pulkit Agrawal DiffM 71 365 0 28 Nov 2022
Offline Q-Learning on Diverse Multi-Task Data Both Scales And Generalizes Aviral Kumar Rishabh Agarwal Xinyang Geng George Tucker Sergey Levine OffRL 44 48 0 28 Nov 2022
Adversarial Cheap Talk Chris Xiaoxuan Lu Timon Willi Alistair Letcher Jakob N. Foerster AAML 29 17 0 20 Nov 2022
Control Transformer: Robot Navigation in Unknown Environments through PRM-Guided Return-Conditioned Sequence Modeling Daniel Lawson A. H. Qureshi 27 8 0 11 Nov 2022
Bridging the Gap Between Target Networks and Functional Regularization Alexandre Piché Valentin Thomas Joseph Marino Rafael Pardiñas Gian Maria Marconi C. Pal Mohammad Emtiyaz Khan 14 1 0 21 Oct 2022
A Policy-Guided Imitation Approach for Offline Reinforcement Learning Haoran Xu Li Jiang Jianxiong Li Xianyuan Zhan OffRL 28 62 0 15 Oct 2022
Factors of Influence of the Overestimation Bias of Q-Learning Julius Wagenbach M. Sabatelli 20 1 0 11 Oct 2022
Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks Litian Liang Yaosheng Xu Stephen Marcus McAleer Dailin Hu Alexander Ihler Pieter Abbeel Roy Fox OOD 27 16 0 16 Sep 2022
Improved Policy Optimization for Online Imitation Learning J. Lavington Sharan Vaswani Mark Schmidt OffRL 28 6 0 29 Jul 2022
Multi-objective Optimization of Notifications Using Offline Reinforcement Learning Prakruthi Prabhakar Yiping Yuan Guangyu Yang Wensheng Sun A. Muralidharan OffRL 28 6 0 07 Jul 2022
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels Edoardo Cetin Philip J. Ball Steve Roberts Oya Celiktutan 40 36 0 03 Jul 2022
Critic Sequential Monte Carlo Vasileios Lioutas J. Lavington Justice Sefas Matthew Niedoba Yunpeng Liu Berend Zwartsenberg Setareh Dabiri Frank Wood Adam Scibior 52 7 0 30 May 2022
Robust Losses for Learning Value Functions Andrew Patterson Victor Liao Martha White 30 12 0 17 May 2022
deep-significance - Easy and Meaningful Statistical Significance Testing in the Age of Neural Networks Dennis Ulmer Christian Hardmeier J. Frellsen 48 42 0 14 Apr 2022
Bayesian Structure Learning with Generative Flow Networks T. Deleu António Góis Chris C. Emezue M. Rankawat Simon Lacoste-Julien Stefan Bauer Yoshua Bengio BDL 50 145 0 28 Feb 2022
Using Deep Reinforcement Learning with Automatic Curriculum Learning for Mapless Navigation in Intralogistics Honghu Xue Benedikt Hein M. Bakr Georg Schildbach Bengt Abel Elmar Rueckert 16 15 0 23 Feb 2022
Selective Credit Assignment Veronica Chelu Diana Borsa Doina Precup Hado van Hasselt 32 2 0 20 Feb 2022
Uncovering Instabilities in Variational-Quantum Deep Q-Networks Maja Franz Lucas Wolf Maniraman Periyasamy Christian Ufrecht Daniel D. Scherer Axel Plinge Christopher Mutschler Wolfgang Mauerer 36 29 0 10 Feb 2022
Offline Reinforcement Learning for Mobile Notifications Yiping Yuan A. Muralidharan Preetam Nandy Miao Cheng Prakruthi Prabhakar OffRL 36 9 0 04 Feb 2022
Deep Q-learning: a robust control approach B. Varga Balázs Kulcsár M. Chehreghani OOD 30 9 0 21 Jan 2022
Chaining Value Functions for Off-Policy Learning Simon Schmitt John Shawe-Taylor Hado van Hasselt OffRL 28 2 0 17 Jan 2022
DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization Aviral Kumar Rishabh Agarwal Tengyu Ma Aaron Courville George Tucker Sergey Levine OffRL 31 65 0 09 Dec 2021
The Impact of Data Distribution on Q-learning with Function Approximation Pedro P. Santos Diogo S. Carvalho Alberto Sardinha Francisco S. Melo OffRL 19 2 0 23 Nov 2021
Hybrid BYOL-ViT: Efficient approach to deal with small datasets Safwen Naimi Rien van Leeuwen W. Souidène S. B. Saoud SSL ViT 25 2 0 08 Nov 2021
Off-Policy Correction for Deep Deterministic Policy Gradient Algorithms via Batch Prioritized Experience Replay Dogan C. Cicek Enes Duran Baturay Saglam Furkan B. Mutlu Suleyman Serdar Kozat OffRL 33 11 0 02 Nov 2021
The Difficulty of Passive Learning in Deep Reinforcement Learning Georg Ostrovski Pablo Samuel Castro Will Dabney OffRL 24 57 0 26 Oct 2021
PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method Ziwei Guan Tengyu Xu Yingbin Liang 26 4 0 13 Oct 2021
On the Estimation Bias in Double Q-Learning Zhizhou Ren Guangxiang Zhu Haotian Hu Beining Han Jian-Hai Chen Chongjie Zhang 24 17 0 29 Sep 2021
Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey Richard Dazeley Peter Vamplew Francisco Cruz 32 60 0 20 Aug 2021
Convergent and Efficient Deep Q Network Algorithm Zhikang T. Wang Masahito Ueda 27 12 0 29 Jun 2021
Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment Michael Chang Sid Kaushik Sergey Levine Thomas Griffiths 31 8 0 28 Jun 2021
Training Larger Networks for Deep Reinforcement Learning Keita Ota Devesh K. Jha Asako Kanezaki OffRL 37 39 0 16 Feb 2021
Self-supervised Graph Representation Learning via Bootstrapping Feihu Che Guohua Yang Dawei Zhang J. Tao Pengpeng Shao Tong Liu SSL 8 23 0 10 Nov 2020
Single and Multi-Agent Deep Reinforcement Learning for AI-Enabled Wireless Networks: A Tutorial Amal Feriani Ekram Hossain 40 237 0 06 Nov 2020