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On Rate-Distortion Theory in Capacity-Limited Cognition & Reinforcement
  Learning

On Rate-Distortion Theory in Capacity-Limited Cognition & Reinforcement Learning

30 October 2022
Dilip Arumugam
Mark K. Ho
Noah D. Goodman
Benjamin Van Roy
ArXivPDFHTML

Papers citing "On Rate-Distortion Theory in Capacity-Limited Cognition & Reinforcement Learning"

4 / 4 papers shown
Title
Satisficing Exploration for Deep Reinforcement Learning
Satisficing Exploration for Deep Reinforcement Learning
Dilip Arumugam
Saurabh Kumar
Ramki Gummadi
Benjamin Van Roy
42
1
0
16 Jul 2024
GLIMPSE: Pragmatically Informative Multi-Document Summarization for
  Scholarly Reviews
GLIMPSE: Pragmatically Informative Multi-Document Summarization for Scholarly Reviews
Maxime Darrin
Ines Arous
Pablo Piantanida
Jackie CK Cheung
55
2
0
11 Jun 2024
An information-theoretic model of shallow and deep language
  comprehension
An information-theoretic model of shallow and deep language comprehension
Jiaxuan Li
Richard Futrell
24
1
0
13 May 2024
Building machines that adapt and compute like brains
Building machines that adapt and compute like brains
Brenden M. Lake
J. Tenenbaum
AI4CE
FedML
NAI
AILaw
254
890
0
11 Nov 2017
1