Using Tabu Search Algorithm for Map Generation in the Terra Mystica Tabletop Game

TL;DR

This paper explores the use of the Tabu Search algorithm to generate and improve game maps for Terra Mystica, demonstrating its effectiveness in procedural content creation.

Contribution

It applies Tabu Search to map generation in Terra Mystica, analyzing how list and neighborhood sizes affect map quality, which is a novel approach in this context.

Findings

Tabu Search effectively generates improved game maps.

Map quality depends on Tabu list and neighborhood sizes.

Proposed method is feasible for procedural map generation.

Abstract

Tabu Search (TS) metaheuristic improves simple local search algorithms (e.g. steepest ascend hill-climbing) by enabling the algorithm to escape local optima points. It has shown to be useful for addressing several combinatorial optimization problems. This paper investigates the performance of TS and considers the effects of the size of the Tabu list and the size of the neighbourhood for a procedural content generation, specifically the generation of maps for a popular tabletop game called Terra Mystica. The results validate the feasibility of the proposed method and how it can be used to generate maps that improve existing maps for the game.