Cellular automata for real-time generation of infinite cave levels

This paper presents a reliable and efficient approach to procedurally generating level maps based on the self-organization capabilities of cellular automata (CA). A simple CA-based algorithm is evaluated on an infinite cave game, generating playable and well-designed tunnel-based maps. The algorithm has very low computational cost, permitting realtime content generation, and the proposed map representation provides sufficient flexibility with respect to level design.peer-reviewe

Spicing up map generation

We describe a search-based map generator for the classic real-time strategy game Dune 2. The generator is capable of creating playable maps in seconds, which can be used with a partial recreation of Dune 2 that has been implemented using the Strategy Game Description Language. Map genotypes are represented as low-resolution matrices, which are then converted to higher-resolution maps through a stochastic process involving cellular automata. Map phenotypes are evaluated using a set of heuristics based on the gameplay requirements of Dune 2.peer-reviewe

SentientWorld : human-based procedural cartography - an experiment in interactive sketching and iterative refining

This paper presents a first step towards a computer-assisted design tool for the creation of game maps. The tool, named Sentient World, allows the designer to draw a rough terrain sketch, adding extra levels of detail through stochastic and gradient search. Novelty search generates a number of dissimilar artificial neural networks that are trained to approximate a designer’s sketch and provide maps of higher resolution back to the designer. As the procedurally generated maps are presented to the designer (to accept, reject, or edit) the terrain sketches are iteratively refined into complete high resolution maps which may diverge from initial designer concepts. Results obtained on a number of test maps show that novelty search is beneficial for introducing divergent content to the designer without reducing the speed of iterative map refinement.This research was supported, in part, by the FP7 ICT project SIREN (project no: 258453).peer-reviewe

Designer-driven 3D buildings generated using variable neighborhood search

This paper presents a mechanism to generate virtual buildings considering designer constraints and guidelines. This mechanism is implemented as a pipeline of different Variable Neighborhood Search (VNS) optimization processes in which several subproblems are tackled (1) rooms locations, (2) connectivity graph, and (3) element placement. The core VNS algorithm includes some variants to improve its performance, such as, for example constraint handling and biased operator selection. The optimization process uses a toolkit of construction primitives implemented as "smart objects" providing basic elements such as rooms, doors, staircases and other connectors. The paper also shows experimental results of the application of different designer constraints to a wide range of buildings from small houses to a large castle with several underground levels

An Efficient Approach of Sokoban Level Generation

This article describes an algorithm for the procedural generation of the Sokoban puzzle. This algorithm can generate Sokoban levels according to the given parameters. The algorithm is meant to generate Sokoban levels efficiently but maintains acceptable quality. This article provides evidence that this algorithm is efficient and produces levels with a quality comparable with other existing levels which can be found online.The approach contains two parts. They are forward process and backward process. The forward process creates the goal position and empty room for the result. And the backward process makes initial status further away from its goal status. In each iteration of the forward or backward process, a box and a direction will be selected based on the strategies being set in the generator parameters. The number iterations are able to be configured by changing the parameters. With certain configuration, the generated levels can be with acceptable average quality. The detailed explanations are also included in this article

Virtual Forestry Generation: Evaluating Models for Tree Placement in Games

A handful of approaches have been previously proposed to generate procedurally virtual forestry for virtual worlds and computer games, including plant growth models and point distribution methods. However, there has been no evaluation to date which assesses how effective these algorithms are at modelling real-world phenomena. In this paper, we tackle this issue by evaluating three algorithms used in the generation of virtual forests—a randomly uniform point distribution method (control), a plant competition model, and an iterative random point distribution technique. Our results show that a plant competition model generated more believable content when viewed from an aerial perspective. Interestingly, however, we also found that a randomly uniform point distribution method produced forestry which was rated higher in playability and photorealism, when viewed from a first-person perspective. We conclude that the objective of the game designer is important to consider when selecting an algorithm to generate forestry, as the algorithms produce forestry that is perceived differently

Procedural content generation of virtual terrain for games

Abstract. Game developers use Procedural Content Generation (PCG) in aid of game development to reduce costs, reach better memory consumption, increase creativity, and augment our limited human imagination by generating content algorithmically. Virtual terrain is one of the main topics of PCG; how well do these techniques support the special needs of game level design? To answer this question, a literature review was conducted to analyse correlation between the capabilities of various PCG-techniques and the needs of level design patterns. We observed that techniques permitting higher degree of local control increased their applicability for virtual terrain in games and that traditional fractal techniques, such as the midpoint displacement method and noise-functions, performed poorly despite their popularity. Our foremost contributions to this field of study were new insights towards more suitable PCG-techniques for use in game development

Генерування ландшафтів для сферичних поверхонь: аналіз завдання та варіанти вирішення

Landscape image quality for spherical surfaces, including planetoids, affects the accuracy of their perception by the users of scientific or educational systems, profitability of games or movies, evolution of relevant software systems. The main issues of available solutions are lack of realism on a big scale, price of full versions of relevant software and absence of tools for conversion from software processing results to planetoids with effective scaling. There are several existing approaches to planetoid landscape generation. Based on a combination of known methods, a solution is proposed, that relies on the use of software agents. The global steps of the designed method consist of preprocessing and generation of planetoids, climate and 3 d models. For planetoid model preprocessing, a convex hull is generated, a set of software agents with landscape processing algorithms is chosen and a database is created for generation results. Planetoid generation consists entirely of software agents: filling the hull with substance, generating tectonic plates, smoothing, adding noise, processing landscapes with fractals and creating relief based on neural networks. Climate generation stage includes determining sea level and generating the world ocean, generating climate data, weather biomes and other water reservoirs, applying erosion based on climate simulation and filling landscape with natural life data. The final step is generating the 3d model, during which the landscape is filled with decorations, data samples are created based on structured user queries, 3d models are generated based on user requests, data is visualized with occlusion culling optimization. Unlike known solutions, where data layers are atomic and their altering requires full landscape recalculation every time, our proposed method allows to freely modify the influence of one software agent on the others, while dividing layers into sublayers. Software agents during processing use two- or three-dimensional masks, which are required in order to control the influence of each software agent on the model as a whole. The advantage is the automatization and the parameterization of detailed planetoid landscape generation with further serialization and processing. This area of research is promising, because on one side, it is necessary to improve the look of models, while on the other side, it is desirable not to go beyond the possible number of calculations. In other words, there is a demand for new models and more optimized algorithms.Проаналізовано проблему генерування ландшафтів за наявними методами для порівняння їх можливостей, виділено основні переваги і недоліки. Розглянуто програмні інструменти, які дають змогу генерувати ландшафти для різних поверхонь. Запропоновано власний метод на підставі поєднання методів, описаних у науковій літературі, який дає змогу гнучко керувати кількісними та якісними показниками моделювання ландшафтів для сферичних поверхонь завдяки введенню параметрів впливу. Зміст методу полягає у застосуванні програмних агентів для відповідного створення складових моделі, а саме – генерування планетоїда, клімату та моделі ландшафту загалом. Для попереднього оброблення моделі планетоїда здійснюють генерування опуклої оболонки та виконують вибір програмних агентів з алгоритмами для оброблення ландшафтів, а також створення бази даних для зберігання всіх результатів. Програмні агенти під час оброблення використовують маски, які потрібні для контролю впливу кожного програмного агента на модель ландшафту загалом. На відміну від відомих рішень, де шари є неподільні і їхня зміна щоразу вимагає повного перерахунку всього ландшафту, запропонований метод дає змогу вільно модифікувати вплив одних агентів на інші на підставі задавання різних масок, а також ділити створені шари на підрівні. Завдяки введенню програмних агентів і масок метод автоматизовано здійснює параметризацію процесу генерування ландшафтів деталізованих планетоїдів з подальшою їх серіалізацією та обробленням. Застосування програмних агентів дає змогу забезпечити гнучкість методу (урахування різних параметрів моделі планетоїда за різного порядку застосування програмних агентів), економічність виконання обчислень (для різної деталізації сегментів сферичної поверхні не потрібні обчислення з "нуля"). Перевагами запропонованого рішення є врахування різних деталей для забезпечення високої реалістичності результату та уникнення зайвих обчислень для різних рівнів зближення огляду поверхонь