Socially-conditioned task reasoning for a virtual tutoring agent

Zian Zhao, Michael Madaio, Florian Pecune, Yoichi Matsuyama, Justine Cassell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Virtual agents have been shown to be more effective when incorporating social factors such as trust into task action selection. However, there has been less work on how virtual tutoring agents can incorporate social factors into pedagogical action selection. We propose and evaluate how a socially-conditioned task reasoner for a virtual pedagogical agent can incorporate both task and social factors into task reasoning. Our work contributes to the autonomous agent community by providing further evidence that incorporating information about dyadic social factors (e.g. rapport) can be beneficial for agents' task reasoning in the case of a tutoring agent.

Original languageEnglish
Title of host publication17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages2265-2267
Number of pages3
ISBN (Print)9781510868083
Publication statusPublished - 2018 Jan 1
Externally publishedYes
Event17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018 - Stockholm, Sweden
Duration: 2018 Jul 102018 Jul 15

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume3
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

Conference17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018
Country/TerritorySweden
CityStockholm
Period18/7/1018/7/15

Keywords

  • Pedagogical agent
  • Rapport
  • RL-LSTM
  • Socially-aware

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

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