Alexander Zook

ABSTRACT Games often interweave a story and series of skill-based events into a complete sequence—a mission. An automated mission generator for skill-based games is one way to synthesize designer requirements with player differences to create missions tailored to each player.

Abstract Computer role playing games engage players through interleaved story and open-ended game play. We present an approach to procedurally generating, rendering, and making playable novel games based on a priori unknown story structures. These stories may be authored by humans or by computational story generation systems. Our approach couples player, designer, and algorithm to generate a novel game using preferences for game play style, general design aesthetics, and a novel story structure.

Abstract We address the problem of building computational agents that are capable of play. Existing research has examined the forms, characteristics, and processes involved in various kinds of play at a high level. However, this research does not provide a unified framework at a level of detail sufficient for building computational agents that can play. As a step toward addressing this gap we synthesize diverse research on pretend play to recognize important components of pretend play agents.

Abstract Many computer games of all genres pit the player against a succession of increasingly difficult challenges such as combat with computer-controlled enemies and puzzles. Part of the fun of computer games is to master the skills necessary to complete the game. Challenge tailoring is the problem of matching the difficulty of skill-based events over the course of a game to a specific player's abilities. We present a tensor factorization approach to predicting player performance in skill-based computer games.

Abstract Scenario-based training exemplifies the learning-by-doing approach to human performance improvement. In this paper, we enumerate the advantages of incorporating automated scenario generation technologies into the traditional scenario development pipeline.

Abstract Conceptual blending has been proposed as a creative cognitive process, but most theories focus on the analysis of existing blends rather than mechanisms for the efficient construction of novel blends. While conceptual blending is a powerful model for creativity, there are many challenges related to the computational application of blending. Inspired by recent theoretical research, we argue that contexts and context-induced goals provide insights into algorithm design for creative systems using conceptual blending.