Deep Variational Reinforcement Learning for POMDPs

6 June 2018

Papers citing "Deep Variational Reinforcement Learning for POMDPs"

46 / 46 papers shown

Title
Autonomous Driving at Unsignalized Intersections: A Review of Decision-Making Challenges and Reinforcement Learning-Based Solutions Mohammad K. Al-Sharman Luc Edes Bert Sun Vishal Jayakumar Mohamed A. Daoud Derek Rayside W. Melek 24 1 0 20 Sep 2024
Learning Online Belief Prediction for Efficient POMDP Planning in Autonomous Driving Zhiyu Huang Chen Tang Chen Lv Masayoshi Tomizuka Wei Zhan 32 5 0 27 Jan 2024
Provable Representation with Efficient Planning for Partial Observable Reinforcement Learning Hongming Zhang Tongzheng Ren Chenjun Xiao Dale Schuurmans Bo Dai 45 3 0 20 Nov 2023
Deep Attention Q-Network for Personalized Treatment Recommendation Simin Ma Junghwan Lee N. Serban Shihao Yang OffRL 27 5 0 04 Jul 2023
Seq2Seq Imitation Learning for Tactile Feedback-based Manipulation Wenyan Yang A. Angleraud R. Pieters J. Pajarinen Joni-Kristian Kämäräinen 32 6 0 05 Mar 2023
Training Robots to Evaluate Robots: Example-Based Interactive Reward Functions for Policy Learning Kun-Yen Huang E. Hu Dinesh Jayaraman OffRL 26 5 0 17 Dec 2022
Recurrent networks, hidden states and beliefs in partially observable environments Gaspard Lambrechts Adrien Bolland D. Ernst 8 12 0 06 Aug 2022
Does Self-supervised Learning Really Improve Reinforcement Learning from Pixels? Xiang Li Jinghuan Shang Srijan Das Michael S. Ryoo SSL 27 31 0 10 Jun 2022
Deep Transformer Q-Networks for Partially Observable Reinforcement Learning Kevin Esslinger Robert W. Platt Chris Amato OffRL 27 32 0 02 Jun 2022
Flow-based Recurrent Belief State Learning for POMDPs Xiaoyu Chen Yao Mu Ping Luo Sheng Li Jianyu Chen 43 18 0 23 May 2022
A Temporal-Pattern Backdoor Attack to Deep Reinforcement Learning Yinbo Yu Jiajia Liu Shouqing Li Ke Huang Xudong Feng AAML 28 11 0 05 May 2022
Training and Evaluation of Deep Policies using Reinforcement Learning and Generative Models Ali Ghadirzadeh Petra Poklukar Karol Arndt Chelsea Finn Ville Kyrki Danica Kragic Marten Bjorkman OffRL 22 1 0 18 Apr 2022
Bellman Meets Hawkes: Model-Based Reinforcement Learning via Temporal Point Processes C. Qu Xiaoyu Tan Siqiao Xue X. Shi James Y. Zhang Hongyuan Mei OffRL 22 17 0 29 Jan 2022
Dynamic programming with incomplete information to overcome navigational uncertainty in a nautical environment Chris Beeler Xinkai Li C. Bellinger Mark Crowley M. Fraser Isaac Tamblyn 27 1 0 29 Dec 2021
Compositional Learning-based Planning for Vision POMDPs Sampada Deglurkar M. H. Lim Johnathan Tucker Zachary Sunberg Aleksandra Faust Claire Tomlin 35 4 0 17 Dec 2021
Sparsely Changing Latent States for Prediction and Planning in Partially Observable Domains Christian Gumbsch Martin Volker Butz Georg Martius AI4CE 18 21 0 29 Oct 2021
Bayesian Sequential Optimal Experimental Design for Nonlinear Models Using Policy Gradient Reinforcement Learning Wanggang Shen Xun Huan 11 39 0 28 Oct 2021
Context-Specific Representation Abstraction for Deep Option Learning Marwa Abdulhai Dong-Ki Kim Matthew D Riemer Miao Liu Gerald Tesauro Jonathan P. How OffRL 29 9 0 20 Sep 2021
Sublinear Regret for Learning POMDPs Yi Xiong Ningyuan Chen Xuefeng Gao Xiang Zhou 21 25 0 08 Jul 2021
Evaluating the progress of Deep Reinforcement Learning in the real world: aligning domain-agnostic and domain-specific research J. Luis E. Crawley B. Cameron OffRL 25 6 0 07 Jul 2021
Differentiable Particle Filtering without Modifying the Forward Pass Adam Scibior Frank D. Wood 23 19 0 18 Jun 2021
Hierarchical and Partially Observable Goal-driven Policy Learning with Goals Relational Graph Xin Ye Yezhou Yang 19 22 0 01 Mar 2021
Training a Resilient Q-Network against Observational Interference Chao-Han Huck Yang I-Te Danny Hung Ouyang Yi Pin-Yu Chen OOD 18 14 0 18 Feb 2021
Online Service Migration in Mobile Edge with Incomplete System Information: A Deep Recurrent Actor-Critic Learning Approach Jin Wang Jia Hu Geyong Min Qiang Ni Tarek A. El-Ghazawi 21 28 0 16 Dec 2020
Learning Latent Representations to Influence Multi-Agent Interaction Annie Xie Dylan P. Losey R. Tolsma Chelsea Finn Dorsa Sadigh DRL 13 132 0 12 Nov 2020
MELD: Meta-Reinforcement Learning from Images via Latent State Models Tony Zhao Anusha Nagabandi Kate Rakelly Chelsea Finn Sergey Levine OffRL 11 36 0 26 Oct 2020
Multimodal Sensor Fusion with Differentiable Filters Michelle A. Lee Brent Yi Roberto Martín-Martín Silvio Savarese Jeannette Bohg 11 59 0 25 Oct 2020
Mastering Atari with Discrete World Models Danijar Hafner Timothy Lillicrap Mohammad Norouzi Jimmy Ba DRL 30 809 0 05 Oct 2020
Data-efficient visuomotor policy training using reinforcement learning and generative models Ali Ghadirzadeh Petra Poklukar Ville Kyrki Danica Kragic Mårten Björkman OffRL 34 9 0 26 Jul 2020
Skill Discovery of Coordination in Multi-agent Reinforcement Learning Shuncheng He Jianzhun Shao Xiangyang Ji 13 7 0 07 Jun 2020
Maximizing Information Gain in Partially Observable Environments via Prediction Reward Yash Satsangi Sungsu Lim Shimon Whiteson F. Oliehoek Martha White 19 15 0 11 May 2020
Causally Correct Partial Models for Reinforcement Learning Danilo Jimenez Rezende Ivo Danihelka George Papamakarios Nan Rosemary Ke Ray Jiang ... Jane X. Wang Jovana Mitrović F. Besse Ioannis Antonoglou Lars Buesing AI4TS 16 32 0 07 Feb 2020
POPCORN: Partially Observed Prediction COnstrained ReiNforcement Learning Joseph D. Futoma M. C. Hughes Finale Doshi-Velez OffRL 13 49 0 13 Jan 2020
Variational Recurrent Models for Solving Partially Observable Control Tasks Dongqi Han Kenji Doya Jun Tani DRL OffRL 8 59 0 23 Dec 2019
Scaling active inference Alexander Tschantz Manuel Baltieri A. Seth Christopher L. Buckley BDL AI4CE 11 68 0 24 Nov 2019
Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges Lei Lei Yue Tan Kan Zheng Shiwen Liu K. Zheng Xuemin Shen Shen OffRL 19 202 0 22 Jul 2019
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model Alex X. Lee Anusha Nagabandi Pieter Abbeel Sergey Levine OffRL BDL 25 371 0 01 Jul 2019
Learning Causal State Representations of Partially Observable Environments Amy Zhang Zachary Chase Lipton Luis Villaseñor-Pineda Kamyar Azizzadenesheli Anima Anandkumar Laurent Itti Joelle Pineau Tommaso Furlanello CML 27 49 0 25 Jun 2019
Learning Belief Representations for Imitation Learning in POMDPs Tanmay Gangwani Joel Lehman Qiang Liu Jian Peng 24 36 0 22 Jun 2019
Meta reinforcement learning as task inference Jan Humplik Alexandre Galashov Leonard Hasenclever Pedro A. Ortega Yee Whye Teh N. Heess OffRL 13 127 0 15 May 2019
Safe Reinforcement Learning with Scene Decomposition for Navigating Complex Urban Environments Maxime Bouton A. Nakhaei K. Fujimura Mykel J. Kochenderfer 12 78 0 25 Apr 2019
Fast Efficient Hyperparameter Tuning for Policy Gradients Supratik Paul Vitaly Kurin Shimon Whiteson 11 32 0 18 Feb 2019
Robust Reinforcement Learning in POMDPs with Incomplete and Noisy Observations Yuhui Wang Hao He Xiaoyang Tan 23 9 0 15 Feb 2019
Neural Predictive Belief Representations Z. Guo M. G. Azar Bilal Piot Bernardo Avila-Pires Rémi Munos SSL 11 80 0 15 Nov 2018
Learning to Drive in a Day Alex Kendall Jeffrey Hawke David Janz Przemyslaw Mazur Daniele Reda John M. Allen Vinh-Dieu Lam Alex Bewley Amar Shah 17 639 0 01 Jul 2018
Temporal Difference Variational Auto-Encoder Karol Gregor George Papamakarios F. Besse Lars Buesing Theophane Weber DRL 16 126 0 08 Jun 2018