Bayesian Reinforcement Learning with Limited Cognitive Load

5 May 2023

Papers citing "Bayesian Reinforcement Learning with Limited Cognitive Load"

25 / 25 papers shown

Title
Reinforcement learning Florentin Wörgötter 82 2,544 0 16 May 2024
The Statistical Complexity of Interactive Decision Making Dylan J. Foster Sham Kakade Jian Qian Alexander Rakhlin 329 178 0 27 Dec 2021
Generalized Kernel Thinning Raaz Dwivedi Lester W. Mackey 80 30 0 04 Oct 2021
People construct simplified mental representations to plan Mark K. Ho David Abel Carlos G. Correa Michael L. Littman Jonathan Cohen Thomas Griffiths 45 90 0 14 May 2021
Reinforcement Learning, Bit by Bit Xiuyuan Lu Benjamin Van Roy Vikranth Dwaracherla M. Ibrahimi Ian Osband Zheng Wen 44 70 0 06 Mar 2021
Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent States Shi Dong Benjamin Van Roy Zhengyuan Zhou 49 31 0 10 Feb 2021
Deciding What to Learn: A Rate-Distortion Approach Dilip Arumugam Benjamin Van Roy 37 24 0 15 Jan 2021
The Value Equivalence Principle for Model-Based Reinforcement Learning Christopher Grimm André Barreto Satinder Singh David Silver OffRL 40 85 0 06 Nov 2020
Mirror Descent and the Information Ratio Tor Lattimore András Gyorgy 38 42 0 25 Sep 2020
Goal-Aware Prediction: Learning to Model What Matters Suraj Nair Silvio Savarese Chelsea Finn 62 65 0 14 Jul 2020
Model-Based Reinforcement Learning with Value-Targeted Regression Alex Ayoub Zeyu Jia Csaba Szepesvári Mengdi Wang Lin F. Yang OffRL 83 304 0 01 Jun 2020
The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget Anirudh Goyal Yoshua Bengio M. Botvinick Sergey Levine 57 24 0 24 Apr 2020
Towards a Quantum-Like Cognitive Architecture for Decision-Making Falk Lieder Lauren Fell Shahram Dehdashti Thomas Griffiths Andreas Wichert AI4CE 43 267 0 11 May 2019
Exploiting Hierarchy for Learning and Transfer in KL-regularized RL Dhruva Tirumala Hyeonwoo Noh Alexandre Galashov Leonard Hasenclever Arun Ahuja Greg Wayne Razvan Pascanu Yee Whye Teh N. Heess OffRL 46 45 0 18 Mar 2019
An Information-Theoretic Approach to Minimax Regret in Partial Monitoring Tor Lattimore Csaba Szepesvári 35 70 0 01 Feb 2019
Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds Andrea Zanette Emma Brunskill OffRL 95 276 0 01 Jan 2019
Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review Sergey Levine AI4CE BDL 73 671 0 02 May 2018
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning Christoph Dann Tor Lattimore Emma Brunskill 72 308 0 22 Mar 2017
Deep Exploration via Randomized Value Functions Ian Osband Benjamin Van Roy Daniel Russo Zheng Wen 89 304 0 22 Mar 2017
Reinforcement Learning with Deep Energy-Based Policies Tuomas Haarnoja Haoran Tang Pieter Abbeel Sergey Levine 95 1,339 0 27 Feb 2017
The Predictron: End-To-End Learning and Planning David Silver H. V. Hasselt Matteo Hessel Tom Schaul A. Guez ... Gabriel Dulac-Arnold David P. Reichert Neil C. Rabinowitz André Barreto T. Degris 62 291 0 28 Dec 2016
Why is Posterior Sampling Better than Optimism for Reinforcement Learning? Ian Osband Benjamin Van Roy BDL 76 259 0 01 Jul 2016
Algorithms for multi-armed bandit problems Volodymyr Kuleshov Doina Precup 116 350 0 25 Feb 2014
Thompson Sampling for Complex Bandit Problems Aditya Gopalan Shie Mannor Yishay Mansour 136 202 0 03 Nov 2013
Sample Complexity of Multi-task Reinforcement Learning Emma Brunskill Lihong Li 79 138 0 26 Sep 2013