The Heuristics of Automatic Story Generation

The intelligence of a story-generating computer program can be assessed in terms of creativity, aesthetic awareness, and understanding. The following approaches are evaluated with respect to these three criteria: simple transition networks, grammar-driven models, simulations, algorithms based on problem-solving techniques, and algorithms driven by so-called "authorial goals." The most serious deficiency of the discussed programs resides in the domain of aesthetic awareness. In order to improve on this situation, story-generation should not follow a strictly linear, chronological order, but rather proceed from the middle outwards, starting with the episodes that bear the focus of interest. The program should select as top-evel goal the creation of climactic situations, create the preparatory events through backward logic, and take the story to the next highlight, or to an appropriate conclusion through a guided simulation. This strategy is ilustrated in a "reverse-engineering," or generative reading of Little Red Riding Hood that simulates the reasoning of an imaginary computer program.

(Source: Author's website)