Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning

4 June 2022

Papers citing "Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning"

6 / 6 papers shown

Title
Toward Efficient Exploration by Large Language Model Agents Dilip Arumugam Thomas L. Griffiths LLMAG 89 0 0 29 Apr 2025
Meta-Gradient Search Control: A Method for Improving the Efficiency of Dyna-style Planning Bradley Burega John D. Martin Luke Kapeluck Michael H. Bowling 32 0 0 27 Jun 2024
On Bits and Bandits: Quantifying the Regret-Information Trade-off Itai Shufaro Nadav Merlis Nir Weinberger Shie Mannor 33 0 0 26 May 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
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
Regret Bounds for Information-Directed Reinforcement Learning Botao Hao Tor Lattimore OffRL 39 17 0 09 Jun 2022