Sarah the virtual advisor to reduce study stress

Ranjbartabar, H; Richards, D; Kutay, C; Mascarenhas, S

Sarah the virtual advisor to reduce study stress

Ranjbartabar, H Richards, D Kutay, C

Mascarenhas, S

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, 2018, 3 pp. 1829 - 1831
Issue Date:: 2018-01-01

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Field	Value	Language
dc.contributor.author	Ranjbartabar, H	en_US
dc.contributor.author	Richards, D	en_US
dc.contributor.author	Kutay, C https://orcid.org/0000-0002-6682-979X	en_US
dc.contributor.author	Mascarenhas, S	en_US
dc.date.issued	2018-01-01	en_US
dc.identifier.citation	Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, 2018, 3 pp. 1829 - 1831	en_US
dc.identifier.isbn	9781510868083	en_US
dc.identifier.issn	1548-8403	en_US
dc.identifier.uri	http://hdl.handle.net/10453/131735
dc.description.abstract	© 2018 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved. Understanding users could help Intelligent Virtual Agents (IVAs) to provide supportive tailored behaviours. To exhibit appropriate behaviours, the IVA needs to adapt based on features of the human that are important for the current context and the purpose of the agent. Towards creation of a user model that the agent can reason over and adapt accordingly, we have created the "Reduce Study Stress" scenario to identify possible relationships and rules based on personality, character preferences and the emotional state of the user. We measured preferences, helpfulness, rapport and emotional feeling and responses to some of the IVAs dialogue. We found differences in preferences and the emotional feeling reported by participants based on individual differences and groups.	en_US
dc.relation.ispartof	Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS	en_US
dc.title	Sarah the virtual advisor to reduce study stress	en_US
dc.type	Conference Proceeding
utslib.citation.volume	3	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Professional Practice and Leadership
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	3	en_US

Abstract:

© 2018 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved. Understanding users could help Intelligent Virtual Agents (IVAs) to provide supportive tailored behaviours. To exhibit appropriate behaviours, the IVA needs to adapt based on features of the human that are important for the current context and the purpose of the agent. Towards creation of a user model that the agent can reason over and adapt accordingly, we have created the "Reduce Study Stress" scenario to identify possible relationships and rules based on personality, character preferences and the emotional state of the user. We measured preferences, helpfulness, rapport and emotional feeling and responses to some of the IVAs dialogue. We found differences in preferences and the emotional feeling reported by participants based on individual differences and groups.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/131735