Illuminating the Space of Dungeon Maps, Locked-door Missions and Enemy Placement Through MAP-Elites

TL;DR

This paper presents an enhanced procedural dungeon generator using MAP-Elites, producing diverse, playable levels with locked-door missions and enemies, validated through computational and user evaluations.

Contribution

It introduces a novel MAP-Elites-based evolutionary approach for dungeon generation, ensuring diverse and feasible levels with player-validated quality.

Findings

High convergence of the MAP-Elites population in dungeon generation

Players enjoyed the generated levels and found them indistinguishable from handcrafted ones

The approach effectively produces diverse and playable dungeon layouts

Abstract

Procedural Content Generation (PCG) methods are valuable tools to speed up the game development process. Moreover, PCG may also present in games as features, such as the procedural dungeon generation (PDG) in Moonlighter (Digital Sun, 2018). This paper introduces an extended version of an evolutionary dungeon generator by incorporating a MAP-Elites population. Our dungeon levels are discretized with rooms that may have locked-door missions and enemies within them. We encoded the dungeons through a tree structure to ensure the feasibility of missions. We performed computational and user feedback experiments to evaluate our PDG approach. They show that our approach accurately converges almost the whole MAP-Elite population for most executions. Finally, players' feedback indicates that they enjoyed the generated levels, and they could not indicate an algorithm as a level generator.