Implementation and Analysis of a Non-deterministic Drama Manager

Abstract

Adaptive interactive storytelling is a resource used to guide the player through the game narrative in a way he/she can understand, in his/her own unique way, the multifaceted nature of the story being told. In interactive storytelling, the player is presented with a set of options to help direct the narrative, and the Drama Manager (DM) is responsible for controlling the narrative trajectories the user will experience. This work proposes a DM based on a genetic algorithm, which will be able to present non-deterministic plot lines to the player, increasing replayability. The proposed DM will follow the Anthropological Structures of the Imaginary proposed by Durand to guide the narrative, which will be the basis for a player model. Experiments were performed both with synthetic datasets as well as eleven players. The results show the GA finds subsets of plot lines that are not far from the optimum while increasing replayability. Qualitative analyses of the players preference considering the three regiments that defined Durand’s theory show it is appropriate to model the players preferences in interactive storytelling.