'Association for the Advancement of Artificial Intelligence (AAAI)'
Abstract
A bottleneck in interactive storytelling is the authorial
burden of writing narrative units, and connecting
them to the interactive narrative structure. To address
this problem, we present a hybrid approach that combines
AI planning and evolutionary optimization in order
to generated new plan operators representing possible
story actions, within the framework of a planningbased
interactive narrative system. We focus our work
on inventing plan operators that are useful for contributing
to suspenseful interactive stories, using suspense
metrics that have been proposed in the literature.We devise
an encoding scheme for converting a plan operator
into a genetic-algorithm chromosome and vice versa,
respecting constraints that are needed for an operator
to be well-formed. We discuss the performance of the
system, and several examples from preliminary experiments
carried out to evaluate the evolved operators.This work has been supported in part by the EU FP7 ICT
project SIREN (project no: 258453). We thank Arnav Jhala
at UC Santa Cruz, and Antonios Liapis and Julian Togelius
at IT University of Copenhagen for the discussion.peer-reviewe
