Adapting Procedural Content Generation to Player Personas Through Evolution

TL;DR

This paper presents a method for evolving game levels tailored to specific player personas using an architecture with persona agents and experience metrics, demonstrated in the game 'Grave Rave' with successful persona-specific adaptations.

Contribution

The paper introduces a novel architecture that adapts procedurally generated levels to individual player personas through evolution, ensuring persona-specific content.

Findings

Successfully adapted levels for four different persona agents

Levels are persona-conscious and not just metric optimizations

Demonstrated effectiveness in the game 'Grave Rave'

Abstract

Automatically adapting game content to players opens new doors for game development. In this paper we propose an architecture using persona agents and experience metrics, which enables evolving procedurally generated levels tailored for particular player personas. Using our game, "Grave Rave", we demonstrate that this approach successfully adapts to four rule-based persona agents over three different experience metrics. Furthermore, the adaptation is shown to be specific in nature, meaning that the levels are persona-conscious, and not just general optimizations with regard to the selected metric.