Date of Submission

Spring 2024

Academic Program

Computer Science

Project Advisor 1

Kerri-Ann Norton

Abstract/Artist's Statement

This project attempts to improve Non-Player Character (NPC) realism in video games by using an Agent-Based Model (ABM) to automate their communication and interactions. To evaluate how information spreads through interacting NPCs in video games, this simulation assumes that the main purpose of NPC societies is to provide a context in which NPCs interact with each other to spread information about player-generated events that change the game state. The goal is to successfully identify possible programming methods to automate NPC behavior and create a more realistic gaming experience for players. The simulation incorporates three archetypal types of characters that are present in most Role-Playing Games (RPGs): merchants, guards, and civilians that spread rumors and antirumors. The behavior of the NPCs is changed by incorporating dynamic movement, different probabilities of rumor-spreading and antirumor-spreading, and believability among different NPC types. The data collected from these interactions, such as the ratio of rumor-spreading agents, are compared to a study on social media rumor- spreading. This ensures that the data can be compared to “real world” statistics regarding rumor-spreading; the more similarities that exist between the data sets support the theory that the automated interactions between NPCs in the simulation are realistic. Using agent-based models to automate NPC interactions can be helpful for future game developers trying to optimize NPC behavior in order to create smarter and more interesting NPCs, thus creating a better, more immersive game experience.

Open Access Agreement

Open Access

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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