TY - JOUR
T1 - Towards Social Situation Awareness in Support Agents
AU - Kola, Ilir
AU - Murukannaiah, Pradeep
AU - Jonker, Catholijn M.
AU - Van Riemsdijk, Birna
PY - 2022
Y1 - 2022
N2 - Artificial agents that support people in their daily activities (e.g., virtual coaches and personal assistants) are increasingly prevalent. Since many daily activities are social in nature, support agents should understand a user's social situation to offer comprehensive support. However, there are no systematic approaches for developing support agents that are social situation aware. We identify key requirements for a support agent to be social situation aware and propose steps to realize those requirements. These steps are presented through a conceptual architecture centered on two key ideas: (1) conceptualizing social situation awareness as an instantiation of Endsley's situation awareness, and (2) using situation taxonomies for such instantiation. This enables support agents to represent a user's social situation, comprehend its meaning, and assess its impact on the user's behavior. We discuss empirical results supporting the effectiveness of the proposed approach and illustrate how the architecture can be used in support agents through two use cases.
AB - Artificial agents that support people in their daily activities (e.g., virtual coaches and personal assistants) are increasingly prevalent. Since many daily activities are social in nature, support agents should understand a user's social situation to offer comprehensive support. However, there are no systematic approaches for developing support agents that are social situation aware. We identify key requirements for a support agent to be social situation aware and propose steps to realize those requirements. These steps are presented through a conceptual architecture centered on two key ideas: (1) conceptualizing social situation awareness as an instantiation of Endsley's situation awareness, and (2) using situation taxonomies for such instantiation. This enables support agents to represent a user's social situation, comprehend its meaning, and assess its impact on the user's behavior. We discuss empirical results supporting the effectiveness of the proposed approach and illustrate how the architecture can be used in support agents through two use cases.
UR - http://www.scopus.com/inward/record.url?scp=85127504159&partnerID=8YFLogxK
U2 - 10.1109/MIS.2022.3163625
DO - 10.1109/MIS.2022.3163625
M3 - Article
AN - SCOPUS:85127504159
JO - IEEE Intelligent Systems
JF - IEEE Intelligent Systems
SN - 1541-1672
ER -