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

7 April 2016

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

10 / 10 papers shown

Title
Variational Inference for Model-Free and Model-Based Reinforcement Learning Felix Leibfried OffRL 13 0 0 04 Sep 2022
Model-Free Risk-Sensitive Reinforcement Learning Grégoire Delétang Jordi Grau-Moya M. Kunesch Tim Genewein Rob Brekelmans Shane Legg Pedro A. Ortega OOD 8 9 0 04 Nov 2021
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 Felix Leibfried Vincent Dutordoir S. T. John N. Durrande GP 42 49 0 27 Dec 2020
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 Heinke Hihn Daniel A. Braun 29 16 0 03 Nov 2020
An Information-theoretic On-line Learning Principle for Specialization in Hierarchical Decision-Making Systems Heinke Hihn Sebastian Gottwald Daniel A. Braun 22 16 0 26 Jul 2019
Balancing Two-Player Stochastic Games with Soft Q-Learning Jordi Grau-Moya Felix Leibfried Haitham Bou-Ammar 22 42 0 09 Feb 2018
An Information-Theoretic Optimality Principle for Deep Reinforcement Learning Felix Leibfried Jordi Grau-Moya Haitham Bou-Ammar 30 24 0 06 Aug 2017
Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach Yinlam Chow Aviv Tamar Shie Mannor Marco Pavone 73 310 0 06 Jun 2015