Towards Social Situation Awareness in Support Agents
This addresses the problem of enhancing support agents for users in social daily activities, but it is incremental as it builds on existing situation awareness concepts.
The paper tackles the lack of systematic approaches for developing support agents that understand social situations, proposing a conceptual architecture based on general situation awareness and situation taxonomies to enable agents to represent, comprehend, and assess social contexts, with empirical results supporting its effectiveness.
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 `general' 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.