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Closing the Learning-Planning Loop with Predictive State Representations

Closing the Learning-Planning Loop with Predictive State Representations

12 December 2009
Byron Boots
S. Siddiqi
Geoffrey J. Gordon
ArXivPDFHTML

Papers citing "Closing the Learning-Planning Loop with Predictive State Representations"

28 / 28 papers shown
Title
LLM-Guided Probabilistic Program Induction for POMDP Model Estimation
LLM-Guided Probabilistic Program Induction for POMDP Model Estimation
Aidan Curtis
Hao Tang
Thiago Veloso
Kevin Ellis
Joshua B. Tenenbaum
Tomás Lozano-Pérez
Leslie Pack Kaelbling
68
0
0
04 May 2025
Provable Benefits of Multi-task RL under Non-Markovian Decision Making
  Processes
Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes
Ruiquan Huang
Yuan-Chia Cheng
Jing Yang
Vincent Tan
Yingbin Liang
26
0
0
20 Oct 2023
Deep Occupancy-Predictive Representations for Autonomous Driving
Deep Occupancy-Predictive Representations for Autonomous Driving
Eivind Meyer
Lars Frederik Peiss
Matthias Althoff
31
3
0
07 Mar 2023
Reward-Mixing MDPs with a Few Latent Contexts are Learnable
Reward-Mixing MDPs with a Few Latent Contexts are Learnable
Jeongyeol Kwon
Yonathan Efroni
C. Caramanis
Shie Mannor
27
5
0
05 Oct 2022
Sequence Model Imitation Learning with Unobserved Contexts
Sequence Model Imitation Learning with Unobserved Contexts
Gokul Swamy
Sanjiban Choudhury
J. Andrew Bagnell
Zhiwei Steven Wu
OffRL
13
25
0
03 Aug 2022
PAC Reinforcement Learning for Predictive State Representations
PAC Reinforcement Learning for Predictive State Representations
Wenhao Zhan
Masatoshi Uehara
Wen Sun
Jason D. Lee
31
38
0
12 Jul 2022
Computationally Efficient PAC RL in POMDPs with Latent Determinism and
  Conditional Embeddings
Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings
Masatoshi Uehara
Ayush Sekhari
Jason D. Lee
Nathan Kallus
Wen Sun
58
6
0
24 Jun 2022
Provably Efficient Reinforcement Learning in Partially Observable
  Dynamical Systems
Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems
Masatoshi Uehara
Ayush Sekhari
Jason D. Lee
Nathan Kallus
Wen Sun
OffRL
49
31
0
24 Jun 2022
Sequential Density Estimation via Nonlinear Continuous Weighted Finite
  Automata
Sequential Density Estimation via Nonlinear Continuous Weighted Finite Automata
Tianyu Li
Bogdan Mazoure
Guillaume Rabusseau
13
0
0
08 Jun 2022
Reinforcement Learning in Reward-Mixing MDPs
Reinforcement Learning in Reward-Mixing MDPs
Jeongyeol Kwon
Yonathan Efroni
C. Caramanis
Shie Mannor
25
15
0
07 Oct 2021
A Spectral Approach to Off-Policy Evaluation for POMDPs
A Spectral Approach to Off-Policy Evaluation for POMDPs
Yash Nair
Nan Jiang
OffRL
21
17
0
22 Sep 2021
Control-Oriented Model-Based Reinforcement Learning with Implicit
  Differentiation
Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation
Evgenii Nikishin
Romina Abachi
Rishabh Agarwal
Pierre-Luc Bacon
OffRL
41
34
0
06 Jun 2021
RL for Latent MDPs: Regret Guarantees and a Lower Bound
RL for Latent MDPs: Regret Guarantees and a Lower Bound
Jeongyeol Kwon
Yonathan Efroni
C. Caramanis
Shie Mannor
19
77
0
09 Feb 2021
Deep Visual Reasoning: Learning to Predict Action Sequences for Task and
  Motion Planning from an Initial Scene Image
Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image
Danny Driess
Jung-Su Ha
Marc Toussaint
LRM
13
100
0
09 Jun 2020
Neural Predictive Belief Representations
Neural Predictive Belief Representations
Z. Guo
M. G. Azar
Bilal Piot
Bernardo Avila-Pires
Rémi Munos
SSL
11
80
0
15 Nov 2018
Connecting Weighted Automata and Recurrent Neural Networks through
  Spectral Learning
Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning
Guillaume Rabusseau
Tianyu Li
Doina Precup
28
41
0
04 Jul 2018
Data-driven Planning via Imitation Learning
Data-driven Planning via Imitation Learning
Sanjiban Choudhury
M. Bhardwaj
S. Arora
Ashish Kapoor
G. Ranade
S. Scherer
Debadeepta Dey
41
80
0
17 Nov 2017
Predictive-State Decoders: Encoding the Future into Recurrent Networks
Predictive-State Decoders: Encoding the Future into Recurrent Networks
Arun Venkatraman
Nicholas Rhinehart
Wen Sun
Lerrel Pinto
M. Hebert
Byron Boots
Kris M. Kitani
J. Andrew Bagnell
AI4CE
13
42
0
25 Sep 2017
Unsupervised state representation learning with robotic priors: a
  robustness benchmark
Unsupervised state representation learning with robotic priors: a robustness benchmark
Timothée Lesort
Mathieu Seurin
Xinrui Li
Natalia Díaz Rodríguez
David Filliat
SSL
DRL
14
32
0
15 Sep 2017
Experimental results : Reinforcement Learning of POMDPs using Spectral
  Methods
Experimental results : Reinforcement Learning of POMDPs using Spectral Methods
Kamyar Azizzadenesheli
A. Lazaric
Anima Anandkumar
11
9
0
07 May 2017
QMDP-Net: Deep Learning for Planning under Partial Observability
QMDP-Net: Deep Learning for Planning under Partial Observability
Peter Karkus
David Hsu
Wee Sun Lee
PINN
22
156
0
20 Mar 2017
Deep Visual Foresight for Planning Robot Motion
Deep Visual Foresight for Planning Robot Motion
Chelsea Finn
Sergey Levine
19
776
0
03 Oct 2016
Learning from the Hindsight Plan -- Episodic MPC Improvement
Learning from the Hindsight Plan -- Episodic MPC Improvement
Aviv Tamar
G. Thomas
Tianhao Zhang
Sergey Levine
Pieter Abbeel
19
64
0
28 Sep 2016
A PAC RL Algorithm for Episodic POMDPs
A PAC RL Algorithm for Episodic POMDPs
Z. Guo
Shayan Doroudi
Emma Brunskill
16
55
0
25 May 2016
Predictable Feature Analysis
Predictable Feature Analysis
Stefan Richthofer
Laurenz Wiskott
30
29
0
11 Nov 2013
Hilbert Space Embeddings of Predictive State Representations
Hilbert Space Embeddings of Predictive State Representations
Byron Boots
Geoffrey J. Gordon
A. Gretton
44
95
0
26 Sep 2013
Two-Manifold Problems
Two-Manifold Problems
Byron Boots
Geoffrey J. Gordon
36
1
0
29 Dec 2011
Multi-timescale Nexting in a Reinforcement Learning Robot
Multi-timescale Nexting in a Reinforcement Learning Robot
Joseph Modayil
Adam White
R. Sutton
60
130
0
06 Dec 2011
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