Personality and Mood for Non-Player Characters: A Method for Behavior Simulation in a Maze Environment
Available at: https://digitalcommons.calpoly.edu/theses/2406
Date of Award
MS in Computer Science
College of Engineering
College of Engineering
When it comes to video games, immersion is key. All types of games aim to keep the player immersed in some form or another. A common aspect of the immersive world in most role-playing games -- but not exclusive to the genre -- is the non-playable character (NPC). At their best, NPCs play an integral role to the sense of immersion the player feels by behaving in a way that feels believable and fits within the world of the game. However, due to lack of innovation in this area of video games, at their worst NPCs can jar the player out of the immersive state of flow with unnatural behavior.
In an effort towards making non-playable characters (NPCs) in games smarter, more believable, and more immersive, a method based in psychological theory for controlling the behavior of NPCs was developed. Based on a behavior model similar to most modern games, our behavior model for NPCs traverses a behavior tree. A novel method was introduced using the five-factor model of personality (also known as the big-five personality traits) and the circumplex model of affect (a model of emotion) to inform the traversal of the behavior tree of NPCs. This behavior model has two main beneficial outcomes. The first is emergent gameplay, resulting in unplanned, unpredictable experiences in games which feel closer to natural behavior, leading to an increase in immersion. This can be used for complex storytelling as well by offering information about an NPC's personality to be used in the narrative of games. Secondly, the model is able to provide the emotional status of an NPC in real time. This capability allows developers to programmatically display facial and body expression, eschewing the current time-consuming approach of artist-choreographed animation. Finally, a maze simulation environment was constructed to test the results of our behavior model and procedural animation.
The data collected from 100 iterations in our maze simulation environment about our behavior model found that a correlation can be observed between traits and actions, showing that emergent gameplay can be achieved by varying personality traits. Additionally, by incorporating a novel method for procedural animation based on real-time emotion data, a more realistic representation of human behavior is achieved.
Applied Behavior Analysis Commons, Computational Engineering Commons, Experimental Analysis of Behavior Commons, Human Factors Psychology Commons