Automatic Game World Generation for Platformer Games Using Genetic Algorithm

Most of the games rely on the game designer to design the level and environment. Increasing of game environment space scale followed by increasing of time and cost. Procedural Content Generation (PCG) is a method to solve this problem by generating a game environment space. In this paper, a PCG method proposed using a genetic algorithm approach to solve the problem in generating game environment. Transition graph adapted in the proposed method to make PCG generate difficulty level. The Index-based approach used to display the biome sequence. This approach displays the biome according to its index in the sequence

Automatic Game World Generation for Platformer Games Using Genetic Algorithm

Most of the games rely on the game designer to design the level and environment. Increasing of game environment space scale followed by increasing of time and cost. Procedural Content Generation (PCG) is a method to solve this problem by generating a game environment space. In this paper, a PCG method proposed using a genetic algorithm approach to solve the problem in generating game environment. Transition graph adapted in the proposed method to make PCG generate difficulty level. The Index-based approach used to display the biome sequence. This approach displays the biome according to its index in the sequence

Node-Based Native Solution to Procedural Game Level Generation

A Geração Procedural de Conteúdo (PCG) aplicada ao domínio do desenvolvimento de jogos tem se tornado um tópico proeminente, com um número crescente de implementações e aplicações. Soluções de PCG standalone e plugin, regidas por interfaces baseadas em nós e outros modelos de alto nível, enfrentam limitações em termos de integração, interatividade e responsividade quando inseridas no processo de desenvolvimento de jogos. Essas limitações afetam a experiência do utilizador e inibem o verdadeiro potencial que estes sistemas podem oferecer. Adotando uma metodologia de Action-Research, realizou-se um estudo preliminar com entrevistas a especialistas da área. A avaliação da pertinência desta metodologia nativa e da abordagem visual mais adequada para a sua interface foi efetuada através de uma série de protótipos. Posteriormente, foi implementado um protótipo funcional e conduzido um estudo de caso com uma amostra constituída por um grupo de especialistas em PCG e de desenvolvedores de jogos. Os participantes realizaram uma série de exercícios que estavam documentados com os respetivos tutoriais. Após a conclusão dos exercícios propostos, os participantes avaliaram a relevância da solução e da experiência do utilizador através de um questionário. No desenvolvimento de uma metodologia nativa de PCG baseado em nós, integrado no motor de jogo, identificamos limitações e concluímos que existem diversos desafios ainda por superar no que diz respeito a uma implementação completa de um sistema complexo e amplo.Procedural Content Generation (PCG) applied to game development has become a prominent topic with increasing implementations and use cases. However, existing standalone and plugin PCG solutions, which use Node-based interfaces and other high-level approaches, face limitations in integration, interactivity, and responsiveness within the game development pipeline. These limitations hinder the overall user experience and restrain the true potential of PCG systems. Adopting an Action-Research methodology, a preliminary interview was conducted with experts in the field. The relevance assessment of this native methodology and the most suitable visual approach for its interface was carried out through a series of prototypes. Subsequently, a functional prototype was implemented, and a case study was conducted using a sample consisting of a group of PCG experts and game developers. The participants performed a series of exercises documented with the respective tutorials. After completing the exercises, the solution's relevancy and user experience were evaluated through a questionnaire. In developing a native node-based PCG methodology integrated into the game engine, we identified limitations. We concluded that several challenges are yet to be overcome regarding fully implementing a complex and extensive system

Evoluindo representações de mapas para o jogo Cube 2 : Sauerbraten

Monografia (graduação)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Ciência da Computação, 2015.Este trabalho apresenta alternativas às representações de mapas introduzidos no artigo “Evolving Interesting Maps for a First Person Shooter”, de Luigi Cardamone et al.. Representação de mapas é utilizado para facilitar ou diminuir os custos de desenvolvimento para Jogos de Tiro em Primeira Pessoa. Para esta monografia, desenvolvemos quatro representações de mapas que aderem as técnicas de projeto de níveis do jogo Cube 2: Sauerbraten (C2) descritas por Marc Saltzman em Secrets of the sages: Level design. Visando possibilitar a comparação das representações, implementamos três das quatro representações de mapas descritas em “Evolving Interesting Maps for a First Person Shooter” bem como as representações propostas nesta monografia. Dessa forma, tornouse possível realizar experimentos de comparação baseadas nas mesmas métricas e testes usados por Luigi Cardamone et al.. Os resultados das comparações demonstram que as representações de mapas desenvolvidas para esta monografia podem ser utilizadas como alternativas as descritas em “Evolving Interesting Maps for a First Person Shooter”.This work attempts to create alternative map representations to the ones presented in the research “Evolving Interesting Maps for a First Person Shooter” [5] utilized to facilitate or lessen the development costs of First Person Shooter (FPS)es. We propose four representations that follow the design techniques for the game Cube 2: Sauerbraten (C2) as described by [36], these will be compared to three of the four map representations described in [5] with the same metrics and tests. These comparisons gave us results that show that our map representations can be used as viable alternatives to the ones described in

Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm

Abstract— Online transportation has become a basic requirement of the general public in support of all activities to go to work, school or vacation to the sights. Public transportation services compete to provide the best service so that consumers feel comfortable using the services offered, so that all activities are noticed, one of them is the search for the shortest route in picking the buyer or delivering to the destination. Node Combination method can minimize memory usage and this methode is more optimal when compared to A* and Ant Colony in the shortest route search like Dijkstra algorithm, but can’t store the history node that has been passed. Therefore, using node combination algorithm is very good in searching the shortest distance is not the shortest route. This paper is structured to modify the node combination algorithm to solve the problem of finding the shortest route at the dynamic location obtained from the transport fleet by displaying the nodes that have the shortest distance and will be implemented in the geographic information system in the form of map to facilitate the use of the system. Keywords— Shortest Path, Algorithm Dijkstra, Node Combination, Dynamic Location (key words