RL4HCI: Reinforcement Learning for Humans, Computers, and Interaction

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

Research output: Contribution to conferenceAbstractScientificpeer-review

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.

Original languageEnglish
Number of pages3
DOIs
Publication statusPublished - May 2021
MoE publication typeNot Eligible
EventACM SIGCHI Annual Conference on Human Factors in Computing Systems - Virtual, Online
Duration: 8 May 202113 May 2021
https://chi2021.acm.org/

Conference

ConferenceACM SIGCHI Annual Conference on Human Factors in Computing Systems
Abbreviated titleACM CHI
CityVirtual, Online
Period08/05/202113/05/2021
Internet address

Keywords

  • applications
  • cognitive models
  • interative Artificial Intelligence
  • MDP
  • model-based/model free
  • POMDP
  • reinforcement learning

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