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A Unified Bellman Optimality Principle Combining Reward Maximization and
  Empowerment

A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment

26 July 2019
Felix Leibfried
Sergio Pascual-Diaz
Jordi Grau-Moya
ArXivPDFHTML

Papers citing "A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment"

6 / 6 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
13
0
0
04 Sep 2022
Backprop-Free Reinforcement Learning with Active Neural Generative
  Coding
Backprop-Free Reinforcement Learning with Active Neural Generative Coding
Alexander Ororbia
A. Mali
41
15
0
10 Jul 2021
Which Mutual-Information Representation Learning Objectives are
  Sufficient for Control?
Which Mutual-Information Representation Learning Objectives are Sufficient for Control?
Kate Rakelly
Abhishek Gupta
Carlos Florensa
Sergey Levine
SSL
23
38
0
14 Jun 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 through Active Inference
Reinforcement Learning through Active Inference
Alexander Tschantz
Beren Millidge
A. Seth
Christopher L. Buckley
AI4CE
26
69
0
28 Feb 2020
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