The Value of Information When Deciding What to Learn

26 October 2021

Papers citing "The Value of Information When Deciding What to Learn"

10 / 10 papers shown

Title
Satisficing Exploration for Deep Reinforcement Learning Dilip Arumugam Saurabh Kumar Ramki Gummadi Benjamin Van Roy 34 1 0 16 Jul 2024
Exploration Unbound Dilip Arumugam Wanqiao Xu Benjamin Van Roy 31 0 0 16 Jul 2024
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
Causal Semantic Communication for Digital Twins: A Generalizable Imitation Learning Approach Christo Kurisummoottil Thomas Walid Saad Yong Xiao 31 20 0 25 Apr 2023
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
Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning Dilip Arumugam Benjamin Van Roy OffRL 23 14 0 04 Jun 2022
Between Rate-Distortion Theory & Value Equivalence in Model-Based Reinforcement Learning Dilip Arumugam Benjamin Van Roy OffRL 26 1 0 04 Jun 2022
Contextual Information-Directed Sampling Botao Hao Tor Lattimore Chao Qin 37 13 0 22 May 2022
Non-Stationary Bandit Learning via Predictive Sampling Yueyang Liu Kuang Xu Benjamin Van Roy 14 19 0 04 May 2022
An Experimental Design Perspective on Model-Based Reinforcement Learning Viraj Mehta Biswajit Paria J. Schneider Stefano Ermon W. Neiswanger OffRL 11 18 0 09 Dec 2021