Configuring Multiple Instances with Multi-Configuration
  Configuration is a successful application area of Artificial Intelligence. In
the majority of the cases, configuration systems focus on configuring one
solution (configuration) that satisfies the preferences of a single user or a
group of users. In this paper, we introduce a new configuration approach -
multi-configuration - that focuses on scenarios where the outcome of a
configuration process is a set of configurations. Example applications thereof
are the configuration of personalized exams for individual students, the
configuration of project teams, reviewer-to-paper assignment, and hotel room
assignments including individualized city trips for tourist groups. For
multi-configuration scenarios, we exemplify a constraint satisfaction problem
representation in the context of configuring exams. The paper is concluded with
a discussion of open issues for future work.
