Reinforcement Learning, Bit by Bit

6 March 2021

Papers citing "Reinforcement Learning, Bit by Bit"

20 / 20 papers shown

Title
Toward Efficient Exploration by Large Language Model Agents Dilip Arumugam Thomas L. Griffiths LLMAG 92 0 0 29 Apr 2025
Value of Information and Reward Specification in Active Inference and POMDPs Ran Wei 49 3 0 13 Aug 2024
Three Dogmas of Reinforcement Learning David Abel Mark K. Ho A. Harutyunyan 38 5 0 15 Jul 2024
Information-Theoretic Foundations for Neural Scaling Laws Hong Jun Jeon Benjamin Van Roy 19 1 0 28 Jun 2024
Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent Yingru Li Jiawei Xu Lei Han Zhi-Quan Luo BDL OffRL 23 6 0 05 Feb 2024
An Invitation to Deep Reinforcement Learning Bernhard Jaeger Andreas Geiger OffRL OOD 78 5 0 13 Dec 2023
A Definition of Continual Reinforcement Learning David Abel André Barreto Benjamin Van Roy Doina Precup H. V. Hasselt Satinder Singh CLL 20 73 0 20 Jul 2023
On the Convergence of Bounded Agents David Abel André Barreto Hado van Hasselt Benjamin Van Roy Doina Precup Satinder Singh 20 4 0 20 Jul 2023
Continual Learning as Computationally Constrained Reinforcement Learning Saurabh Kumar Henrik Marklund Anand Srinivasa Rao Yifan Zhu Hong Jun Jeon Yueyang Liu Benjamin Van Roy CLL 27 22 0 10 Jul 2023
Bayesian Reinforcement Learning with Limited Cognitive Load Dilip Arumugam Mark K. Ho Noah D. Goodman Benjamin Van Roy OffRL 34 8 0 05 May 2023
STEERING: Stein Information Directed Exploration for Model-Based Reinforcement Learning Souradip Chakraborty Amrit Singh Bedi Alec Koppel Mengdi Wang Furong Huang Dinesh Manocha 24 7 0 28 Jan 2023
On learning history based policies for controlling Markov decision processes Gandharv Patil Aditya Mahajan Doina Precup OffRL 21 5 0 06 Nov 2022
On Rate-Distortion Theory in Capacity-Limited Cognition & Reinforcement Learning Dilip Arumugam Mark K. Ho Noah D. Goodman Benjamin Van Roy 28 4 0 30 Oct 2022
Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits Gergely Neu Julia Olkhovskaya Matteo Papini Ludovic Schwartz 31 16 0 27 May 2022
Non-Stationary Bandit Learning via Predictive Sampling Yueyang Liu Kuang Xu Benjamin Van Roy 14 19 0 04 May 2022
Model-Value Inconsistency as a Signal for Epistemic Uncertainty Angelos Filos Eszter Vértes Zita Marinho Gregory Farquhar Diana Borsa A. Friesen Feryal M. P. Behbahani Tom Schaul André Barreto Simon Osindero 44 7 0 08 Dec 2021
The Value of Information When Deciding What to Learn Dilip Arumugam Benjamin Van Roy 16 12 0 26 Oct 2021
The Neural Testbed: Evaluating Joint Predictions Ian Osband Zheng Wen S. Asghari Vikranth Dwaracherla Botao Hao M. Ibrahimi Dieterich Lawson Xiuyuan Lu Brendan O'Donoghue Benjamin Van Roy UQCV 24 21 0 09 Oct 2021
Learning and Information in Stochastic Networks and Queues N. Walton Kuang Xu 6 20 0 18 May 2021
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 120 166 0 06 Jan 2021