Projects
Reading
People
Chat
SU\G
(𝔸)
/K·U
Projects
Reading
People
Chat
Sign Up
Light
Dark
System
Deep Variational Reinforcement Learning for POMDPs
Maximilian Igl
,
Luisa Zintgraf
,
Tuan Anh Le
,
Frank Wood
,
Shimon Whiteson
Type:
Preprint
Publication Date:
2018-06-06
Citations:
14
View Publication
Share
Locations
arXiv (Cornell University) -
View
Similar Works
Action
Title
Year
Authors
+
Deep Variational Reinforcement Learning for POMDPs
2018
Maximilian Igl
Luisa Zintgraf
Tuan Anh Le
Frank Wood
Shimon Whiteson
+
On Improving Deep Reinforcement Learning for POMDPs
2017
Pengfei Zhu
Xin Li
Pascal Poupart
Guanghui Miao
+
Contrastive Variational Model-Based Reinforcement Learning for Complex Observations.
2020
Xiao Ma
Siwei Chen
David Hsu
Wee Sun Lee
+
Discriminative Particle Filter Reinforcement Learning for Complex Partial Observations
2020
Xiao Ma
Péter Karkus
Nan Ye
David Hsu
Wee Sun Lee
+
Discriminative Particle Filter Reinforcement Learning for Complex Partial Observations
2020
Xiao Ma
Péter Karkus
David Hsu
Wee Sun Lee
Nan Ye
+
Learning Markov State Abstractions for Deep Reinforcement Learning
2021
Cameron Allen
Neev Parikh
Omer Gottesman
George Konidaris
+
PDF
Chat
EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning
2025
Siddharth Aravindan
Dixant Mittal
Wee Sun Lee
+
Posterior Sampling for Deep Reinforcement Learning
2023
Remo Sasso
Michelangelo Conserva
Paulo Rauber
+
Flow-based Recurrent Belief State Learning for POMDPs
2022
Xiaoyu Chen
Yao Mu
Ping Luo
Shengbo Eben Li
Jianyu Chen
+
Variational Inference for Data-Efficient Model Learning in POMDPs
2018
Sebastian Tschiatschek
Kai Arulkumaran
Jan Stühmer
Katja Hofmann
+
VIME: Variational Information Maximizing Exploration
2016
Rein Houthooft
Xi Chen
Yan Duan
John Schulman
Filip De Turck
Pieter Abbeel
+
Variational Policy Propagation for Multi-agent Reinforcement Learning
2020
Chao Qu
Hui Li
Chang Liu
Junwu Xiong
James Zhang
Wei Chu
Weiqiang Wang
Yuan Qi
Le Song
+
PDF
Chat
Learning Interpretable Policies in Hindsight-Observable POMDPs through Partially Supervised Reinforcement Learning
2024
M Lanier
Ying Xu
Nathan Jacobs
Chongjie Zhang
Yevgeniy Vorobeychik
+
Outcome-Driven Reinforcement Learning via Variational Inference
2021
Tim G. J. Rudner
Vitchyr H. Pong
Rowan McAllister
Yarin Gal
Sergey Levine
+
Outcome-Driven Reinforcement Learning via Variational Inference
2021
Tim G. J. Rudner
Vitchyr H. Pong
Rowan McAllister
Yarin Gal
Sergey Levine
+
PDF
Chat
Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning
2024
Marvin Alles
Philip Becker-Ehmck
Patrick van der Smagt
Maximilian Karl
+
VIREL: A Variational Inference Framework for Reinforcement Learning
2019
Matthew Fellows
Anuj Mahajan
Tim G. J. Rudner
Shimon Whiteson
+
Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings
2018
John D. Co-Reyes
YuXuan Liu
Abhishek Gupta
Benjamin Eysenbach
Pieter Abbeel
Sergey Levine
+
BADDr: Bayes-Adaptive Deep Dropout RL for POMDPs
2022
Sammie Katt
Hai V. Nguyen
Frans A. Oliehoek
Christopher Amato
+
Towards Boosting the Performance of Deep Reinforcement Learning for Partially Observable Markov Decision Processes
2017
Pengfei Zhu
Xin Li
Pascal Poupart
Works That Cite This (10)
Action
Title
Year
Authors
+
How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?
2021
Jingxi Xu
Bruce Lee
Nikolai Matni
Dinesh Jayaraman
+
PDF
Chat
Scaling Active Inference
2020
Alexander Tschantz
Manuel Baltieri
Anil K. Seth
Christopher L. Buckley
+
Discriminative Particle Filter Reinforcement Learning for Complex Partial Observations
2020
Xiao Ma
Péter Karkus
David Hsu
Wee Sun Lee
Nan Ye
+
Learning to Drive in a Day
2018
Alex Kendall
Jeffrey Hawke
David M. Janz
P. Mazur
Daniele Reda
John-Mark Allen
Vinh-Dieu Lam
Alex Bewley
Amar Shah
+
PDF
Chat
Sublinear regret for learning POMDPs
2022
Yi Xiong
Ningyuan Chen
Xuefeng Gao
Xiang Zhou
+
Optimizing Sequential Medical Treatments with Auto-Encoding Heuristic Search in POMDPs
2019
Luchen Li
Matthieu Komorowski
A. Aldo Faisal
+
Local Information Agent Modelling in Partially-Observable Environments
2020
Georgios Papoudakis
Filippos Christianos
Stefano V. Albrecht
+
Scaling active inference
2019
Alexander Tschantz
Manuel Baltieri
Anil K. Seth
Christopher L. Buckley
+
Meta-Model-Based Meta-Policy Optimization
2020
T. HIRAOKA
Takahisa Imagawa
Voot Tangkaratt
Takayuki Osa
Takashi Onishi
Yoshimasa Tsuruoka
+
Particle Filter Recurrent Neural Networks
2019
Xiao Ma
Péter Karkus
David Hsu
Wee Sun Lee
Works Cited by This (0)
Action
Title
Year
Authors