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Planning with Information-Processing Constraints and Model Uncertainty
  in Markov Decision Processes

Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes

7 April 2016
Jordi Grau-Moya
Felix Leibfried
Tim Genewein
Daniel A. Braun
ArXivPDFHTML

Papers citing "Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes"

12 / 12 papers shown
Title
Variational Inference for Model-Free and Model-Based Reinforcement
  Learning
Variational Inference for Model-Free and Model-Based Reinforcement Learning
Felix Leibfried
OffRL
15
0
0
04 Sep 2022
Model-Free Risk-Sensitive Reinforcement Learning
Model-Free Risk-Sensitive Reinforcement Learning
Grégoire Delétang
Jordi Grau-Moya
M. Kunesch
Tim Genewein
Rob Brekelmans
Shane Legg
Pedro A. Ortega
OOD
10
9
0
04 Nov 2021
Bellman: A Toolbox for Model-Based Reinforcement Learning in TensorFlow
Bellman: A Toolbox for Model-Based Reinforcement Learning in TensorFlow
John Mcleod
Hrvoje Stojić
Vincent Adam
Dongho Kim
Jordi Grau-Moya
Peter Vrancx
Felix Leibfried
OffRL
21
2
0
26 Mar 2021
A Tutorial on Sparse Gaussian Processes and Variational Inference
A Tutorial on Sparse Gaussian Processes and Variational Inference
Felix Leibfried
Vincent Dutordoir
S. T. John
N. Durrande
GP
42
49
0
27 Dec 2020
Reinforcement Learning with Subspaces using Free Energy Paradigm
Reinforcement Learning with Subspaces using Free Energy Paradigm
Milad Ghorbani
Reshad Hosseini
Seyed Pooya Shariatpanahi
M. N. Ahmadabadi
24
0
0
13 Dec 2020
Specialization in Hierarchical Learning Systems
Specialization in Hierarchical Learning Systems
Heinke Hihn
Daniel A. Braun
29
16
0
03 Nov 2020
A Unified Bellman Optimality Principle Combining Reward Maximization and
  Empowerment
A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment
Felix Leibfried
Sergio Pascual-Diaz
Jordi Grau-Moya
23
27
0
26 Jul 2019
An Information-theoretic On-line Learning Principle for Specialization
  in Hierarchical Decision-Making Systems
An Information-theoretic On-line Learning Principle for Specialization in Hierarchical Decision-Making Systems
Heinke Hihn
Sebastian Gottwald
Daniel A. Braun
24
16
0
26 Jul 2019
Bounded Rational Decision-Making with Adaptive Neural Network Priors
Bounded Rational Decision-Making with Adaptive Neural Network Priors
Heinke Hihn
Sebastian Gottwald
Daniel A. Braun
26
10
0
04 Sep 2018
Balancing Two-Player Stochastic Games with Soft Q-Learning
Balancing Two-Player Stochastic Games with Soft Q-Learning
Jordi Grau-Moya
Felix Leibfried
Haitham Bou-Ammar
24
42
0
09 Feb 2018
An Information-Theoretic Optimality Principle for Deep Reinforcement
  Learning
An Information-Theoretic Optimality Principle for Deep Reinforcement Learning
Felix Leibfried
Jordi Grau-Moya
Haitham Bou-Ammar
32
24
0
06 Aug 2017
Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach
Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach
Yinlam Chow
Aviv Tamar
Shie Mannor
Marco Pavone
73
312
0
06 Jun 2015
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