Procedural Content Generation

Ph.D. Quals - Lyra: Simulating Believable Opinionated NPCs (Extended)

This work expands on and extends work previously pubished for the Lyra System towards the Ph.D. Computer Science qualifier requirement at NC State University. We conducted a human-subjects study of Lyra to evaluate the generated conversations and …

Lyra: Simulating Believable Opinionated Virtual Characters

Lyra is a simulation of a opinionated population of virtual characters with inherent biases that can believably debate politically-charged topics. We conducted a human-subjects study to evaluate these generated conversations and affinity groups for their believability and to inform future iterations of the simulation. We believe successful simulation of opinion change in social dynamics provides a foundation for computational recognition, prediction, and interfacing with humans.

Scheduling Live Interactive Narratives with Mixed-Integer Linear Programming

In this paper, we tackle the largely overlooked problem of scheduling a multiplayer interactive narrative and propose the Live Interactive Narrative Scheduling Problem (LINSP), which handles reasoning under temporal uncertainty, resource scheduling, and non-linear plot choices.

Mixed Reality Meets Procedural Content Generation in Video Games

The use of artificial intelligence and procedural content generation algorithms in mixed reality games is an unexplored space. We posit that these algorithms can enhance the gameplay experience in mixed reality games. We present two prototype games …

Procedural Level Generation for Augmented Reality Games

Mixed reality games are those in which virtual graphical assets are overlaid on the physical world. We explore the use of procedural content generation to enhance the gameplay experience in a prototype mixed reality game. Procedural content …