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A method for comparing NPC social ability

The main focus of game developers has for a long time been the audiovisual fidelity of the games, but some researchers claim that artificial intelligence (AI) will be the next step in improving the player experience in games. However, there is as of yet a lack of ways of measuring comparing the believability of non-player character (NPC) behavior in games. In order to rectify this we present a method which can be used to create a typology of NPC behavior believability. Our method uses the Carley & Newell fractionation matrix to describe how advanced the behavior of a game’s NPCs is. This is then recorded in a format that can be compared by simple logic operations.

Analyzing the social dynamics of non-player characters

Much of the current research into artificial intelligence (AI) for computer games has been focused on simple actions performed by the characters in games (such as moving between points or shooting at a target, and other simple strategic actions), or on the overarching structure of the game story. However, we claim that these two separate approaches need to be bridged in order to fully realize the potential of enjoyment in computer games. As such, we have explored the middle ground between the individual action and the story – the type of behavior that occurs in a “scene” within the game. To this end we have established a new model for that can be used to discover in what ways a non-player character acts in ways that break the player’s feeling of immersion in the world.

Does Game Quality Reflect Heuristic Evaluation?: Heuristic Evaluation of Games in Different Quality Strata

Usability evaluation tools in the form of heuristic lists can be very helpful in software development. In the field of video game design, researchers are continuously developing new heuristic tools aimed specifically at video game productions. However, through previous studies, the authors have found that even though these tools are frequent and common, design issues regularly appear in video games. This study examines whether video game heuristics are able to capture and evaluate softer values of video game interaction, based on the challenges, flow and immersion of gameplay. By conducting a heuristic evaluation on low scoring and high scoring games the authors manage to show which kind of design issues are most frequent in both high and low scoring games. As a further result of the study, two new heuristics are presented.

Games for Learning

This chapter discusses educational aspects and possibilities of serious games. For researchers as well as game designers we describe key learning theories to ground their work in theoretical framework. We draw on recent meta-reviews to offer an exhaustive inventory of known learning and affective outcomes in serious games, and to discuss assessment methods valuable not only for research but also for efficient serious game design. The implementation and design of serious games are outlined in separated sections. Different individual characteristics that seem to be strongly affecting process of learning with serious games (learning style, gender and age) are discussed with emphasis on game development.