Special Issue on Reinforcement Learning for Real Life

Guest Editors: Yuxi Li, Alborz Geramifard, Lihong Li, Csaba Szepesvari, Tao Wang

Journal

Machine Learning

Machine Learning is an international forum focusing on computational approaches to learning.

Yuxi Li

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Alborz Geramifard

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Lihong Li

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Csaba Szepesvari

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Tao Wang

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Showing 1-12 of 12 articles

Guest editorial: special issue on reinforcement learning for real life
Yuxi Li
Alborz Geramifard
Tao Wang
EditorialNotes 02 August 2021 Pages: 2291 - 2293
A deep reinforcement learning framework for continuous intraday market bidding
Ioannis Boukas
Damien Ernst
Bertrand Cornélusse
OriginalPaper 12 July 2021 Pages: 2335 - 2387
Air Learning: a deep reinforcement learning gym for autonomous aerial robot visual navigation
Srivatsan Krishnan
Behzad Boroujerdian
Vijay Janapa Reddi
OriginalPaper Open access 07 July 2021 Pages: 2501 - 2540
IntelligentPooling: practical Thompson sampling for mHealth
Sabina Tomkins
Peng Liao
Susan Murphy
OriginalPaper 21 June 2021 Pages: 2685 - 2727
Bandit algorithms to personalize educational chatbots
William Cai
Josh Grossman
Sharad Goel
OriginalPaper 25 May 2021 Pages: 2389 - 2418
Grounded action transformation for sim-to-real reinforcement learning
Josiah P. Hanna
Siddharth Desai
Peter Stone
OriginalPaper Open access 13 May 2021 Pages: 2469 - 2499
Inverse reinforcement learning in contextual MDPs
Stav Belogolovsky
Philip Korsunsky
Tom Zahavy
OriginalPaper Open access 12 May 2021 Pages: 2295 - 2334
Lessons on off-policy methods from a notification component of a chatbot
Scott Rome
Tianwen Chen
Ding Zhou
OriginalPaper 04 May 2021 Pages: 2577 - 2602
Challenges of real-world reinforcement learning: definitions, benchmarks and analysis
Gabriel Dulac-Arnold
Nir Levine
Todd Hester
OriginalPaper 22 April 2021 Pages: 2419 - 2468
Partially observable environment estimation with uplift inference for reinforcement learning based recommendation
Wenjie Shang
Qingyang Li
Jieping Ye
OriginalPaper 14 April 2021 Pages: 2603 - 2640
Automatic discovery of interpretable planning strategies
Julian Skirzyński
Frederic Becker
Falk Lieder
OriginalPaper Open access 09 April 2021 Pages: 2641 - 2683
Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems
Amarildo Likmeta
Alberto Maria Metelli
Marcello Restelli
OriginalPaper Open access 14 March 2021 Pages: 2541 - 2576

Special Issue on Reinforcement Learning for Real Life

Participating journal

Machine Learning

Editors

Yuxi Li

Alborz Geramifard

Lihong Li

Csaba Szepesvari

Tao Wang

Articles

Guest editorial: special issue on reinforcement learning for real life

A deep reinforcement learning framework for continuous intraday market bidding

Air Learning: a deep reinforcement learning gym for autonomous aerial robot visual navigation

IntelligentPooling: practical Thompson sampling for mHealth

Bandit algorithms to personalize educational chatbots

Grounded action transformation for sim-to-real reinforcement learning

Inverse reinforcement learning in contextual MDPs

Lessons on off-policy methods from a notification component of a chatbot

Challenges of real-world reinforcement learning: definitions, benchmarks and analysis

Partially observable environment estimation with uplift inference for reinforcement learning based recommendation

Automatic discovery of interpretable planning strategies

Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems