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"

20 / 20 papers shown

Title
Inverse Decision Modeling: Learning Interpretable Representations of Behavior Daniel Jarrett Alihan Huyuk M. Schaar AI4CE 89 28 0 28 Oct 2023
Beyond Bayes-optimality: meta-learning what you know you don't know Jordi Grau-Moya Grégoire Delétang M. Kunesch Tim Genewein Elliot Catt ... Jane X. Wang Marcus Hutter Christopher Summerfield Shane Legg Pedro A. Ortega 42 1 0 30 Sep 2022
Variational Inference for Model-Free and Model-Based Reinforcement Learning Felix Leibfried OffRL 76 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 84 10 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 63 2 0 26 Mar 2021
A Tutorial on Sparse Gaussian Processes and Variational Inference Felix Leibfried Vincent Dutordoir S. T. John N. Durrande GP 162 52 0 27 Dec 2020
Reinforcement Learning with Subspaces using Free Energy Paradigm Milad Ghorbani Reshad Hosseini Seyed Pooya Shariatpanahi M. N. Ahmadabadi 121 0 0 13 Dec 2020
Specialization in Hierarchical Learning Systems Heinke Hihn Daniel A. Braun 83 16 0 03 Nov 2020
The Two Kinds of Free Energy and the Bayesian Revolution Sebastian Gottwald Daniel A. Braun 3DV 38 33 0 24 Apr 2020
Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning Felix Leibfried Jordi Grau-Moya 74 22 0 11 Sep 2019
A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment Felix Leibfried Sergio Pascual-Diaz Jordi Grau-Moya 110 29 0 26 Jul 2019
An Information-theoretic On-line Learning Principle for Specialization in Hierarchical Decision-Making Systems Heinke Hihn Sebastian Gottwald Daniel A. Braun 84 16 0 26 Jul 2019
Disentangled Skill Embeddings for Reinforcement Learning Janith C. Petangoda Sergio Pascual-Diaz Vincent Adam Peter Vrancx Jordi Grau-Moya DRL OffRL 62 15 0 21 Jun 2019
Robust Reinforcement Learning for Continuous Control with Model Misspecification D. Mankowitz Nir Levine Rae Jeong Yuanyuan Shi Jackie Kay A. Abdolmaleki Jost Tobias Springenberg Timothy A. Mann Todd Hester Martin Riedmiller OOD 128 122 0 18 Jun 2019
Task-Driven Estimation and Control via Information Bottlenecks Vincent Pacelli Anirudha Majumdar 34 12 0 20 Sep 2018
Bounded Rational Decision-Making with Adaptive Neural Network Priors Heinke Hihn Sebastian Gottwald Daniel A. Braun 75 10 0 04 Sep 2018
Balancing Two-Player Stochastic Games with Soft Q-Learning Jordi Grau-Moya Felix Leibfried Haitham Bou-Ammar 122 43 0 09 Feb 2018
AI Safety Gridworlds Jan Leike Miljan Martic Victoria Krakovna Pedro A. Ortega Tom Everitt Andrew Lefrancq Laurent Orseau Shane Legg 158 255 0 27 Nov 2017
Hierarchical State Abstractions for Decision-Making Problems with Computational Constraints Daniel T. Larsson Daniel A. Braun Panagiotis Tsiotras 62 12 0 22 Oct 2017
An Information-Theoretic Optimality Principle for Deep Reinforcement Learning Felix Leibfried Jordi Grau-Moya Haitham Bou-Ammar 101 24 0 06 Aug 2017