Evolving interesting maps for a first person shooter

We address the problem of automatically designing maps for first-person shooter (FPS) games. An efficient solution to this procedural content generation (PCG) problem could allow the design of FPS games of lower development cost with near-infinite replay value and capability to adapt to the skills and preferences of individual players. We propose a search-based solution, where maps are evolved to optimize a fitness function that is based on the players’ average fighting time. For that purpose, four different map representations are tested and compared. Results obtained showcase the clear advantage of some representations in generating interesting FPS maps and demonstrate the promise of the approach followed for automatic level design in that game genre.peer-reviewe

Interfaz automática de generación de niveles en videojuegos para la prueba de algoritmo de hormigas

El juego de los Lemmings fue muy popular en la década de los 90. La temática del juego consiste en superar los diferentes obstáculos de un nivel partiendo desde un punto inicial y alcanzar un punto de salida. Para lograr este objetivo, los Lemmings disponen de distintas habilidades que puedan usar un determinado número de veces, pudiendo modificar el entorno en el que se encuentran, para así poder alcanzar el punto de salida. Distintos métodos de inteligencia artificial son comúnmente usados para la resolución de pantallas. En este trabajo de fin de grado se propone un análisis de distintos algoritmos aplicables a la resolución de los niveles y una batería de pruebas del algoritmo de colonia de hormigas comparando sus resultados con un algoritmo genético. De igual modo, también se va a elaborar un método para la generación aleatoria de pantallas mediante un algoritmo codificado en Python.The videogame “Lemmings” was so popular in 90’s. The game consist of passing different obstacles from a start point and reach an exit point. To achieve this goal, Lemmings have different skills that they can use a determinate number of times with the possibility of change the environment in which they are in order to reach the exit point. Different artificial intelligence methods are commonly used in screen solving. In this paper, different algorithms for screen solving and a battery of tests of ant colony algorithm, comparing their results with a genetic algorithm, are proposed. Similarly, a method for random screen generation is going to be developed in Python