Towards a Model-Learning Approach to Interactive Narrative Intelligence for Opportunistic Storytelling

Opportunistic storytelling is an approach to interactive narrative where the AI challenge is to tell a story about what the player is doing, with game play providing the ordinary activity that underlies story events. In this preliminary work, we motivate the need for event prediction within this framework, and describe a machine learning approach to the problem. We report results showing how different feature models can be learned and compared in this context, towards automating model selection.