Interaction-based Authoring for Scalable Co-creative Agents

نویسندگان

  • Mikhail Jacob
  • Brian Magerko
چکیده

This article presents a novel approach to authoring cocreative systems called interaction-based authoring that combines ideas from case-based learning and imitative learning, while emphasizing its use in open-ended co-creative application domains. This work suggests an alternative to manually authoring knowledge for computationally creative agents that relies on user interaction “in the wild” as opposed to high-effort manual authoring beforehand. The Viewpoints AI installation is described as an instantiation of the interaction-based authoring approach. Finally, the interaction-based authoring approach is evaluated within the Viewpoints AI installation and the results are discussed guiding development and further evaluation in the future.

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تاریخ انتشار 2015