Comparing techniques for the semi-autonomous formation of expert teams

Selecting and scheduling human experts can be a highly complex task, given various constraints (such as on what expertise is needed and when) and preferences (such as which expertise an expert most prefers to exercise). A system of multiple computational agents can thus greatly help users form and schedule expert teams. This paper compares two alternative implementations of such agents, highlighting the strengths and limitations of each. In particular, we describe a new formulation of the team formation and scheduling problem as a Hybrid Scheduling Problem (HSP), empirically demonstrate the promise of this formulation, and highlight how the application of HSP to this problem has led us to identify important modifications to mechanisms that improve HSP solving. Finally, we summarize how the HSP formulation can support a high degree of human-agent collaboration during the process of forming and scheduling expert teams.