RL4HCI: Reinforcement Learning for Humans, Computers, and Interaction

Dorota Glowacka; Andrew Howes; Jussi P. Jokinen; Antti Oulasvirta; Özgür Şimşek

doi:10.1145/3411763.3441323

RL4HCI: Reinforcement Learning for Humans, Computers, and Interaction

Dorota Glowacka, Andrew Howes, Jussi P. Jokinen, Antti Oulasvirta, Özgür Şimşek

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Abstract › Scientific › vertaisarvioitu

3 Sitaatiot (Scopus)

Abstrakti

Reinforcement learning (RL) is emerging as an approach to understand intelligence in both humans and machines. However, if RL is to have a meaningful impact in human-computer interaction, it is critical that these two threads are integrated. This is required for genuinely interactive RL-based systems which take into account user capacities and preferences. This workshop will build a community and form a research agenda for investigating RL in HCI.

Alkuperäiskieli	Englanti
Sivumäärä	3
DOI - pysyväislinkit	https://doi.org/10.1145/3411763.3441323
Tila	Julkaistu - toukok. 2021
OKM-julkaisutyyppi	Ei sovellu
Tapahtuma	ACM SIGCHI Annual Conference on Human Factors in Computing Systems - Virtual, Online, Yokohama, Japani Kesto: 8 toukok. 2021 → 13 toukok. 2021 https://chi2021.acm.org/

Conference

Conference	ACM SIGCHI Annual Conference on Human Factors in Computing Systems
Lyhennettä	ACM CHI
Maa/Alue	Japani
Kaupunki	Yokohama
Ajanjakso	08/05/2021 → 13/05/2021
www-osoite	https://chi2021.acm.org/

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10.1145/3411763.3441323

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title = "RL4HCI: Reinforcement Learning for Humans, Computers, and Interaction",

abstract = "Reinforcement learning (RL) is emerging as an approach to understand intelligence in both humans and machines. However, if RL is to have a meaningful impact in human-computer interaction, it is critical that these two threads are integrated. This is required for genuinely interactive RL-based systems which take into account user capacities and preferences. This workshop will build a community and form a research agenda for investigating RL in HCI.",

keywords = "applications, cognitive models, interative Artificial Intelligence, MDP, model-based/model free, POMDP, reinforcement learning",

author = "Dorota Glowacka and Andrew Howes and Jokinen, {Jussi P.} and Antti Oulasvirta and {\"O}zg{\"u}r {\c S}im{\c s}ek",

note = "Publisher Copyright: {\textcopyright} 2021 Owner/Author. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; ACM SIGCHI Annual Conference on Human Factors in Computing Systems, ACM CHI ; Conference date: 08-05-2021 Through 13-05-2021",

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doi = "10.1145/3411763.3441323",

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TY - CONF

T1 - RL4HCI

T2 - ACM SIGCHI Annual Conference on Human Factors in Computing Systems

AU - Glowacka, Dorota

AU - Howes, Andrew

AU - Jokinen, Jussi P.

AU - Oulasvirta, Antti

AU - Şimşek, Özgür

PY - 2021/5

Y1 - 2021/5

N2 - Reinforcement learning (RL) is emerging as an approach to understand intelligence in both humans and machines. However, if RL is to have a meaningful impact in human-computer interaction, it is critical that these two threads are integrated. This is required for genuinely interactive RL-based systems which take into account user capacities and preferences. This workshop will build a community and form a research agenda for investigating RL in HCI.

AB - Reinforcement learning (RL) is emerging as an approach to understand intelligence in both humans and machines. However, if RL is to have a meaningful impact in human-computer interaction, it is critical that these two threads are integrated. This is required for genuinely interactive RL-based systems which take into account user capacities and preferences. This workshop will build a community and form a research agenda for investigating RL in HCI.

KW - applications

KW - cognitive models

KW - interative Artificial Intelligence

KW - MDP

KW - model-based/model free

KW - POMDP

KW - reinforcement learning

UR - http://www.scopus.com/inward/record.url?scp=85105800847&partnerID=8YFLogxK

U2 - 10.1145/3411763.3441323

DO - 10.1145/3411763.3441323

M3 - Abstract

AN - SCOPUS:85105800847

Y2 - 8 May 2021 through 13 May 2021

ER -

RL4HCI: Reinforcement Learning for Humans, Computers, and Interaction

Abstrakti

Conference

Pääsy asiakirjaan

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