Reinforcement learning with limited reinforcement: Using Bayes risk for active learning in POMDPs

, &
Artificial Intelligence 187-188 (C):115-132 (2012)
  Copy   BIBTEX

Abstract

This article has no associated abstract. (fix it)

Categories

Keywords

Reprint years

DOI

10.1016/j.artint.2012.04.006

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 93,127

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

My notes

Similar books and articles

Negotiating team formation using deep reinforcement learning.Yoram Bachrach, Richard Everett, Edward Hughes, Angeliki Lazaridou, Joel Z. Leibo, Marc Lanctot, Michael Johanson, Wojciech M. Czarnecki & Thore Graepel - 2020 - Artificial Intelligence 288 (C):103356.
Automatic programming of behavior-based robots using reinforcement learning.Sridhar Mahadevan & Jonathan Connell - 1992 - Artificial Intelligence 55 (2-3):311-365.
Reinforcement learning and artificial agency.Patrick Butlin - 2024 - Mind and Language 39 (1):22-38.
Learning reward machines: A study in partially observable reinforcement learning.Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Valenzano, Margarita P. Castro, Ethan Waldie & Sheila A. McIlraith - 2023 - Artificial Intelligence 323 (C):103989.
Using POMDPs for learning cost sensitive decision trees.Shlomi Maliah & Guy Shani - 2021 - Artificial Intelligence 292 (C):103400.
Deep Reinforcement Learning as Foundation for Artificial General Intelligence.Itamar Arel - 2012 - In Pei Wang & Ben Goertzel (eds.), Theoretical Foundations of Artificial General Intelligence. Springer. pp. 89--102.
Decentralized Reinforcement Learning of Robot Behaviors.David L. Leottau, Javier Ruiz-del-Solar & Robert Babuška - 2018 - Artificial Intelligence 256 (C):130-159.
Certified reinforcement learning with logic guidance.Hosein Hasanbeig, Daniel Kroening & Alessandro Abate - 2023 - Artificial Intelligence 322 (C):103949.
Profit Sharing の不完全知覚環境下への拡張: PS-r^* の提案と評価.Kobayashi Shigenobu Miyazaki Kazuteru - 2003 - Transactions of the Japanese Society for Artificial Intelligence 18:286-296.
Counterfactual state explanations for reinforcement learning agents via generative deep learning.Matthew L. Olson, Roli Khanna, Lawrence Neal, Fuxin Li & Weng-Keen Wong - 2021 - Artificial Intelligence 295 (C):103455.

Analytics

Added to PP
2020-12-22

Downloads
7 (#1,413,139)

6 months
7 (#491,177)

Historical graph of downloads
How can I increase my downloads?

Citations of this work

No citations found.

Add more citations

References found in this work

Add more references