Multiagent simulation meets the real world

To realize large scale socially embedded systems, this paper proposes a multiagent-based participatory design that consists of steps called 1) participatory simulation, where scenario-guided agents and human-controlled avatars coexist in virtual space and jointly perform simulations, and 2) augmented experiment, where an experiment is performed in real space by human subjects and scenario-guided extras. In this methodology, we use production rules to describe agent models for approximating users, and multiagent scenarios to describe interaction models among services and their users. To learn agent and interaction models incrementally from simulations and experiments, we establish the participatory design loop with deductive machine learning technologies.