Player Modelling is one of the challenges in Interactive Narratives (INs), where a precise representation of the players mental state is needed to provide a personalised experience. However, how to represent the interaction of the player with the game to make the appropriate decision in the story is still an open question. In this paper, we aim to bridge this gap identifying the information needed to capture the players interaction with an IN using the Belief-Desire-Intention (BDI) model of agency. We present a BDI design to mimic a players interaction with a simplified version of the interactive fiction Anchorhead.

We describe an approach to generating animations of drawings that start as a random collection of strokes and gradually resolve into a recognizable subject. The strokes are represented as tree based genetic programs. An animation is generated by rendering the best individual in a generation as a frame of a movie. The resulting animations have an engaging characteristic in which the target slowly emerges from a random set of strokes. We have generated two qualitatively different kinds of animations, ones that use grey level straight line strokes and ones that use binary Bezier curve stokes. Around 100,000 generations are needed to generate engaging animations. Population sizes of 2 and 4 give the best convergence behaviour. Convergence can be accelerated by using information from the target in drawing a stroke. Our approach provides a large range of creative opportunities for artists. Artists have control over choice of target and the various stroke parameters.

We describe the implementation of an art installation that generates animated photomosaics of the viewer. Photomosaics are target images composed of smaller images known as tiles. When a photomosaic is viewed from afar the detail of the tiles is lost and the target image is evident. Up close, the opposite occurs: the detail of the tiles is evident and the target image is lost. Our system uses a photo of the viewer as the target and miniatures of the viewer's face as tiles. Evolutionary search is used to find the best selection and arrangement of tiles. Each newly found best image is then used as the frame of a movie. The resulting animations start from a random arrangement of tiles and gradually the viewer's face emerges and is clearly visible, and then gradually de-materialises into a random pattern.