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Efforts to “greenshift” (Backe) digital games have been hindered, in part, by a gap between game development practices and critical game studies. To date, plant modeling for games has largely focused on imitating visual patterns rather than implementing dynamic ecological processes, which has shaped and ultimately limited the arguments that games are able to make about the natural world. Propagate, an individual-based plant growth plugin for Unreal Engine, draws from both ecological modeling and game criticism to deepen the relationship between play and ecology. The project offers a speculative approach to cultivating persistent digital environments that vary over time, are delicately interconnected, and exist in dialogue with players. Approaching game worlds as living, animate environments instead of painstakingly crafted backdrops is a step towards redistributing narrative focus and agency from players to the spaces they inhabit.

This work focuses on incorporating style - specifically visual style - into procedural content generation processes. Specifically, I model style as a series of constraints that must be satisfied while an object is generated.

Процедурная генерация, или создание контента во время работы программы, это сложное направление, которое требует не только понимания 3D-графики, но и навыков программирования графики, что часто сводится к изучению работы графических процессоров. Из-за такой сложности разработчики часто используют уже готовые инструменты для создания контента. Такие инструменты обобщают и упрощают работу, предоставляя большой заготовленный набор функции, который можно использовать не зная программирования вовсе. К сожалению, обобщение часто приводит к уменьшению гибкости и вводит новые ограничения. Статистика показывает, что использование процедурной генерации, для создания массивной 3D-геометрии, невозможно при использовании готовых инструментов с уже заготовленными функциями. Такие инструменты не позволяют воплотить огромные масштабы массивной геометрии в жизнь из-за различных ограничений. Кроме того, существующие алгоритмы создания 3D-геометрии часто не учитывают применение этих алгоритмов для создания массивной 3D-геометрии, например, планет. Рассматриваемый в этой работе алгоритм Marching Cubes также не учитывает применение алгоритма для создания массивной геометрии, из-за чего применение этого алгоритма в таких целях будет иметь много ограничений и много недостатков. Но данный алгоритм выбран не случайно, он обладает большой популярностью и мы поговорим почему. Данная работа фокусируется на представлении новой модификации на уже существующий алгоритм Marching Cubes в целях применения его в рамках массивной геометрии. Данный алгоритм найдет применение в компьютерных играх с космической тематикой, наш алгоритм позволяет создавать массивную 3D-геометрию планетарных масштабов даже на слабых компьютерах без особых затрат по ресурсам. Кроме того, наш алгоритм позволяет изменять сгенерированную геометрию в реальном времени, без задержек по времени, что так важно компьютерным играм. Procedural generation, or the creation of content while a program is running, is a complex area that requires not only an understanding of 3D graphics, but also graphics programming skills, which often boils down to learning how GPUs work. Because of this complexity, developers often use off-the-shelf content creation tools. Such tools generalize and simplify work by providing a large pre-built set of functions that can be used without knowing programming at all. Unfortunately, generalization often reduces flexibility and introduces new constraints. Statistics show that using procedural generation to create massive 3D geometry is impossible when using ready-made tools with already prepared functions. Such tools do not allow the huge scales of massive geometry to be brought to life due to various constraints. In addition, existing 3D geometry creation algorithms often do not account for the application of these algorithms to create massive 3D geometry such as planets. The Marching Cubes algorithm considered in this work also does not take into account the use of the algorithm for creating massive geometry, which is why the use of this algorithm for such purposes will have many limitations and many disadvantages. But this algorithm was not chosen by chance, it is very popular and we will talk why. This work focuses on modifying the existing Marching Cubes algorithm to apply it to massive geometry. This algorithm will find application in computer games with a space theme, our algorithm allows to create massive 3D geometry of planetary scales even on a low-end computers without special resource costs. In addition, our algorithm allows to change the generated geometry in real time, without time delays, which is so important for computer games.

With the growing interest in deep learning algorithms and computational design in the architectural field, the need for large, accessible and diverse architectural datasets increases. Due to the complexity of such 3D datasets, the most widespread techniques of 3D scanning and manual building modeling are very time-consuming, which does not allow to have a sufficiently large open-source dataset. We decided to tackle this problem by constructing a field-specific synthetic data generation pipeline that generates an arbitrary amount of 3D data along with the associated 2D and 3D annotations. The variety of annotations, the flexibility to customize the generated building and dataset parameters make this framework suitable for multiple deep learning tasks, including geometric deep learning that requires direct 3D supervision. Creating our building data generation pipeline we leveraged the experts’ architectural knowledge in order to construct a framework that would be modular, extendable and would provide a sufficient amount of class-balanced data samples. Moreover, we purposefully involve the researcher in the dataset customization allowing the introduction of additional building components, material textures, building classes, number and type of annotations as well as the number of views per 3D model sample. In this way, the framework would satisfy different research requirements and would be adaptable to a large variety of tasks. All code and data is made publicly available: https://cdinstitute.github.io/Building-Dataset-Generator/.

This paper presents a novel approach to procedural generation of game maps for multi-player, competitive video games. A multi-agent evolutionary system is employed to place streets, buildings and other items, resulting in a playable video game map. The system utilises computational agents that act in conjunction with the human designer to produce maps that exhibit desirable characteristics. This paper compares the impact that the additional agents have in terms of the quality of candidate solutions. The results indicate that the use of the agents produces higher quality solutions in comparison to a traditional interactive genetic algorithm.

In this article, the author presents a novel approach to the procedural generation of artwork series based on multiple sequence alignment of orthologous gene copies. In the strategy developed, nucleotides present in a string of DNA (A, G, C, T) were each assigned to an existing artwork. New visual compositions were then created by collaging columns of pixels from each of the existing four artworks according to the arrangement of nucleotides after orthologous genes were aligned. The resulting outcome was a distinctive set of artworks in which visual differences were governed by nucleotide divergence at genes of interest due to evolutionary processes.

Organic Art (William Latham and Stephen Todd, 1987) was reincarnated by the same authors with programmer and artist Peter Todd as Mutator2 (2013); Mutator2 was transitioned into VR as Mutator VR (2016) with programmer and artist Lance Putnam. The authors describe the graphics and audio systems of these works, particularly the procedural generation and visual effects and the creative exploitation of these effects within an art installation. The authors mix “real” and “unreal” features and effects, inspired by surrealist art, to create highly immersive psychedelic organic experiences for the viewer-participant. Interface simplicity and discoverability is critical for VR exhibitions, as is the balance between an experience constrained by an artist's choices and a freer (but riskier) one with greater public choice. Public gallery installation of Mutator VR creates special challenges.

Procedural content generation (PCG) methods are commonly employed in computer games, simulations, and other related industries. While these methods are used for levels, terrains, stories and missions, their usage for procedural city generation is relatively rare because cities are heterogeneous structures with different components such as roads, layouts and buildings that depend on and affect each other. Additionally, ancient cities grew organically to areas that are safe and to those that provide food and water. This resulted in cities that do not have apparent regular patterns, such as rectangular building blocks. We propose an approach that uses cellular automata (CA) that generates clusters of areas. The CA is repeated for each cluster to hierarchically create different levels of the city. This procedure creates an organic city layout with fractal properties. The layout specifies the building blocks, main roads, and foliage. We also present a set of methods that can transform this layout into a three-dimensional model of the city. The results are promising; cities can be created in under a minute with minimal required input, and the resulting virtual city looks organic, rather than an algorithmic layout that has repeating patterns.

This article is about the procedural generation of accessible multistory buildings including stairwells. We present an algorithm featuring a natural bottom-up approach, where each building is defined by a set of rooms that can be connected by doors or stairways and are equipped with windows. Our approach is robust so that neither the rooms, nor the connections, nor the objects can be placed in invalid positions. In the second part, we enhance the process by a procedural growth algorithm with automatic corridor detection and stairwell placement. Finally, we propose an automatic mesh generation for either procedurally or manually designed buildings. We evaluate our approach by creating a full implementation of the algorithm, and judge it based on the resulting realism, accessibility, and diversity of a generated test set of buildings.

Results from a triple-blind mixed-method user study into the effectiveness of mixed-initiative tools for the procedural generation of game levels are presented. A tool which generates levels using interactive evolutionary optimisation was designed for this study which (a) is focused on supporting the designer to explore the design space and (b) only requires the designer to interact with it by designing levels. The tool identifies level design patterns in an initial hand-designed map and uses that information to drive an interactive optimisation algorithm. A rigorous user study was designed which compared the experiences of designers using the mixed-initiative tool to designers who were given a tool which provided completely random level suggestions. The designers using the mixed-initiative tool showed an increased engagement in the level design task, reporting that it was effective in inspiring new ideas and design directions. This provides significant evidence that procedural content generation can be used as a powerful tool to support the human design process., Accepted to be Published in: IEEE Transactions on Games

In this paper, we present a system that allows developers to add passive haptic feedback into their virtual reality applications by making use of existing physical objects in the user’s real environment. Our approach has minimal dependence on procedural generation and does not limit the virtual space to the dimensions of the physical play-area.

In industrial applications continuous wireless connectivity of mobile clients can rarely by guaranteed. Lack of communication negatively impacts the performance of industrial automation systems, e.g. Automated Guided Vehicle (AGV) fleets. Utilizing industrial Mobile Ad-hoc NETworks (MANETs) and adaptive positioning systems can reduce the number of disconnections in these AGV fleets. Therefore the performance of the mobile systems (e.g. AGV fleet) is improved and factory efficiency increased. In this work procedural simulation is used to examine wireless communication in industrial applications. This methods enables the observation of the interaction of mobility control system, network status and robotic system performance independently from a specific environment or scenario. Novel insights on the effectiveness of ad-hoc communication in industrial applications and the correlation of AGV fleet connectedness and AGV fleet transport performance are presented. Additionally a control method is proposed, which improves the network coverage of an industrial MANET and efficiency of AGV fleets.

Constraint-based procedural generation has recently had a lot of interest following the publication of the WaveFunctionCollapse (WFC) algorithm, but usability issues have restricted the number of games and projects that have resulted. We present Tessera, a library and tool for WFC specifically designed to address the practical issues that arise from constraint based generation. We discuss the user interface of the tool and useful extensions to the base algorithm of WFC.

When studying robots collaborating with humans, much of the focus has been on robot policies that coordinate fluently with human teammates in collaborative tasks. However, less emphasis has been placed on the effect of the environment on coordination behaviors. To thoroughly explore environments that result in diverse behaviors, we propose a framework for procedural generation of environments that are (1) stylistically similar to human-authored environments, (2) guaranteed to be solvable by the human-robot team, and (3) diverse with respect to coordination measures. We analyze the procedurally generated environments in the Overcooked benchmark domain via simulation and an online user study. Results show that the environments result in qualitatively different emerging behaviors and statistically significant differences in collaborative fluency metrics, even when the robot runs the same planning algorithm., Accepted to Robotics: Science and Systems (RSS) 2021

The Modified Diamond Square algorithm is presented, as a result of which a 3-dimensional map of the fractal surface is obtained. This method of visualization using voxels allows to generate the relief structures (caves, canyons, quarries) that cannot be generated using a regular elevation map. The result of using the modified algorithm is shown on the landscape construction. Мета статті — представлення модифікованого алгоритму Diamond Square, в результаті роботи якого можна отримати тривимірну карту фрактальної поверхні. Методи. У середовищі Unity була створена демонстрація для побудови ігрових рівнів, яка дозволяє будувати карти на основі модифікованого алгоритму Diamond Square. В результаті своєї роботи отримаємо 3-мірну карту фрактальної поверхні, яка може бути використана у майбутніх проектах. Вихідна програма служить для демонстрації роботи алгоритму і ґрунтується на трьох сценаріях: модифікованому алгоритмі Diamond Square, допоміжних алгоритмах обробки і сценаріїв камери. Результати. В статті представлено модифікований алгоритм Diamond Square, в результаті роботи якого отримуємо тривимірну карту фрактальної поверхні. Результат використання модифікованого алгоритму показано на прикладі побудови ландшафтної конструкції. Цель статьи — представление модифицированного алгоритма Diamond Square, в результате работы которого можно получить трехмерную карту фрактальной поверхности. Методы. В среде Unity была создана демонстрация для построения игровых уровней, которая позволяет строить карты на основе модифицированного алгоритма Diamond Square. В результате работы алгоритма получается 3-мерная карта фрактальной поверхности, которая может быть использована в будущих проектах. Исходная программа служит для демонстрации работы алгоритма и основывается на трех сценариях: модифицированном алгоритме Diamond Square, вспомогательных алгоритмах обработки и сценариев камеры. Результаты. В статье представлен модифицированный алгоритм Diamond Square, в результате работы которого получаем трехмерную карту фрактальной поверхности. Результат использования модифицированного алгоритма показан на примере построения ландшафтной конструкции.

In this paper, we try to solve the problem of making video games with multiple storylines. To do this, we developed an algorithm capable of generating variations in the game's story through altering the behaviors of the characters. For this task, we use Q-Learning. Our results indicate that this algorithm may be viable to be used in video games for commercial purposes.

Simulation-based testing is critical for ensuring safety of autonomous vehicles. Autonomous vehicles are enabled by deep learning techniques which require a large quantity of data. With simulation testing, we can create rare events for testing and training of autonomous vehicles. Procedural generation of roads and modeling of driving behaviors in an easily extendable architecture ensures that we are able to create rare scenarios at scale with minimal artistic burden. In this paper, we present CruzWay, a system that both supports and creates these scenarios. With CruzWay, we are able to procedurally generate town sized road networks or road intersections. CruzWay supports generation of road meshes as well as navigation meshes from SUMO road network files. CruzWay can generate cars as well as pedestrians run by behavior trees (BTs) in this environment. The self-contained, modular nature of BTs in combination with procedural roads allows us to create a large number of scenarios.

This paper presents a new approach of heightmap generation for Real-Time Strategy games (RTS) based on Cellular Automata (CA) in the context of various established techniques. The proposed approach uses different CA rulesets to generate and modify maps for the RTS game Supreme Commander. To evaluate the quality of the generated maps, a survey was conducted asking 30 participants about map quality compared to user-generated maps. The participants rated the maps more balanced and novel but less aesthetically pleasing. The paper concludes with according future work propositions to improve the presented approach.

This paper proposes a tool for 3D Procedural Terrain Generation in games. The main objective of this study is to assess the quality of the generated terrains and thus the experience of the user. The tool measures how traversable a terrain is, how long it takes to walk across and how much of it is accessible. The produced results can be used to further refine the generation method. The evaluation consists of multiple terrains being produced, based on Generative Adversarial Networks (GANs) trained on satellite images. A path finding algorithm is then used to evaluate the traversability of each terrain between two points on the map. Results show that the proposed method can generate quite diverse and interesting maps and that the proposed metric can be used for evaluation of playability.

Procedural terrain generation refers to the generation of terrain features, such as landscaping, rivers or road networks, through the use of algorithms, with minimal input required from the user. In the process of game development, generating terrain is often an important part of the game development process. Traditional generation methods are often too time consuming especially with larger terrain maps. On the other hand, procedural methods that generate terrain automatically often do not have much user control over the output. We explore the usage of conditional generative adversarial networks in the creation of road maps, as well as the application of such road maps in the creation of game levels in game development engines such as Unreal Engine 4.

Procedural generation is used to achieve a wide variety of game design goals, and has led to the creation of several game subgenres by injecting variance, surprise or unpredictability into otherwise static designs. Information games are a type of mystery game in which the player is tasked with gathering knowledge and developing an understanding of an event or system. Their reliance on player knowledge leaves them vulnerable to spoilers and hard to replay. In this paper we introduce the notion of a generative forensics game, a subgenre of information games that challenge the player to understand the output of a generative system, and present two examples.

We introduce a novel semi-procedural approach that avoids drawbacks of procedural textures and leverages advantages of data-driven texture synthesis. We split synthesis in two parts: 1) structure synthesis, based on a procedural parametric model and 2) color details synthesis, being data-driven. The procedural model consists of a generic Point Process Texture Basis Function (PPTBF), which extends sparse convolution noises by defining rich convolution kernels. They consist of a window function multiplied with a correlated statistical mixture of Gabor functions, both designed to encapsulate a large span of common spatial stochastic structures, including cells, cracks, grains, scratches, spots, stains, and waves. Parameters can be prescribed automatically by supplying binary structure exemplars. As for noise-based Gaussian textures, the PPTBF is used as stand-alone function, avoiding classification tasks that occur when handling multiple procedural assets. Because the PPTBF is based on a single set of parameters it allows for continuous transitions between different visual structures and an easy control over its visual characteristics. Color is consistently synthesized from the exemplar using a multiscale parallel texture synthesis by numbers, constrained by the PPTBF. The generated textures are parametric, infinite and avoid repetition. The data-driven part is automatic and guarantees strong visual resemblance with inputs. Applications: this work is related to content creation tools for films and video games, especially procedural texture and material synthesis (e.g. Substance Designer), and inverse procedural modeling (e.g inverse shade tree approach). This paper has been published in the CGF journal (Computer Grapics Forum) in July 2020 and presented at the EGSR conference (Eurographics Symposium on Rendering) in July 2020 where it got an award: Honorable Mention from the Best Papers committee.

The use of Procedural Content Generation techniques in the production of Video Games has seen a large diffusion in these last years. Regarding the procedural generation of Computer Graphics content, several works have been proposed about the automatic construction of complex models and environments, or about the instancing of several copies of a reference model, each with peculiar differences to introduce variety. However, very few works have proposed techniques for the procedural production of complex materials to be assigned to these generated models. In this paper, we present a method for the automatic generation of realistic layered materials based on the application of a Genetic Algorithm. We show that, with the proposed approach, is possible to generate several instances of a target material (e.g., a car paint, or a rusty metal), maintaining a desired level of closeness to the overall characteristics of the simulated interaction between the light and the surface, but introducing also a controlled amount of differences in the final reproduction of the perceived appearance.

In this work we present a tool for three-dimensional procedural modelling of flowers based on botanical information. The main biological input is floral formulas. It can represent the structure of a flower with numbers, letters and symbols. Based on this notation, a user-friendly interface was created. Artists need to draw several curves and provide floral formula to create a full 3d model. It speeds up the recreation of biologically-correct models and thanks to its implementation in Maya, each flower can be easily customized after creating initial model.

Building realistic living cities with people inside is useful for many applications like movies, computer games, and virtual reality (VR). However, algorithms that produce (i.e., procedurally generate) endless realistic cities are still scarce when simulating big cities. In this paper, we report on research that explores the design of a city generator algorithm that solves the problem of procedurally generating a realistic 3D endless city from “glueing together” a limited number of city tiles. Additionally, a new kind of pedestrian system is introduced that solves typical performance problems of a baseline pedestrian system. The inner workings of the city generator algorithm are described in detail, and solutions to problems encountered are discussed. We found that the city generator algorithm works in practice using a driving simulator. The research provides new insights into how it is possible to generate realistic endless cities, including simulated pedestrians.

Terrain is an essential part of any outdoor environment and, consequently, many techniques have appeared that deal with the problem of its automatic generation, such as procedural modeling. One form to create terrains is using noise functions because its low computational cost and its random result. However, the randomness of these functions also makes it difficult to have any control over the result obtained. In order to solve the problem of lack of control, this paper presents a new method noise-based that allows procedural terrains creation with elevation constraints (GPS routes, points of interest and areas of interest). For this, the method establishes the restrictions as fixed values in the heightmap function and creates a system of equations to obtain all points that they depend this restrictions. In this way, the terrain obtained maintains the random noise, but including the desired restrictions. The paper also includes how we apply this method on large terrain models without losing resolution or increasing the computational cost excessively. The results show that our method makes it possible to integrate this kind of constraints with high accuracy and realism while preserving the natural appearance of the procedural generation.

This paper consisted in the generation of an evolutionary computation-based system capable of generate and evolve the structures of which one level of the Angry Birds game is composed, these structures are evaluated according to the stability of the structure as well as for the complexity of said structure. For this a level generation system was designed based on the data obtained from the game, said data consist in the number and type of pieces that appear and the applied gravity of the game, the individuals of the group are evaluated by a simulation of the generated level and then checking how the structures are affected by the gravity of the game. The evolutionary computation system as the main objective of generating structures based on the existent pieces of the game and evolving said pieces by combining them in a process that simulates the rules of the Open-Ended Evolution algorithm in which the evolution of this compounds is not inclined towards a numeric objective rather than to extend the diversity from which the pieces may be selected for a level.

We present Honey, I’m Home, a short 2D adventure game which makes use of the SPHINX framework for procedurally generating narrative puzzles. The player guides the protagonist, a journalist for a local newspaper, through four game areas, interacting with numerous characters and objects along the way. The player must solve puzzles to complete each area, combining objects and interacting with characters in the game. The procedural generation of puzzles ensures that while the gameworld remains largely identical between replays, the puzzles encountered are different. The aim of Honey, I’m Home was to serve as a tool for our two-fold evaluation of the SPHINX algorithm, from its functionality in game development, as well as its effect on player experience. To this end a small user study was also conducted on Honey, I’m Home.

A current research topic within virtual reality is to allow the user to move by natural walking in a virtual environment that exceeds the size of the tracking area. Multiple approaches to overlapping architecture dealing with this issue already exist, but they are either custom made for a specific tracking area size or require a tracking area too large to work efficiently for personal use. This paper proposes a method to make scalable overlapping architecture by procedural generation of tile-based mazes that seamlessly teleport the user using portals. We evaluated how the tile size of the overlapping maze affects the user’s spatial awareness of their physical position. 23 participants of Aalborg University students completed the Spatial Awareness Task of finding a tile that overlapped with their starting tile in a 3 \(\times \) 3, 4 \(\times \) 4, and 5 \(\times \) 5 tile maze. Between condition 3 \(\times \) 3 and 5 \(\times \) 5, and condition 4 \(\times \) 4 and 5 \(\times \) 5, participants were more confused in the 5 \(\times \) 5 tile maze compared to 3 \(\times \) 3 (p = .0015) and 4 \(\times \) 4 (p = .0295) tile mazes.

In this paper a comparison of selected algorithms used to procedurally generate terrain for video games is presented. The algorithms’ performance is tested with two implementation environments: Unity and Godot. Results are aggregated and discussed. Conclusions drawn are of two types: intuitive and counter-intuitive.

A key challenge in procedural content generation is to automatically evaluate whether the generated content has good quality. In this paper, we describe an approach that uses nonexpert workers to evaluate small portions of levels generated by an off-the-shelf generation system for the game of Infinite Mario Bros . Several such evaluated portions are then combined to form full levels of the game using a mathematical progression arc model. The composition of the small portions into full levels is done by accounting for the human-annotated information. We evaluated the approach using computational metrics as well as surveying human subjects playing the levels. The results show that the human computation approach is able to generate levels that are perceived by people to have better visual aesthetics and to be more enjoyable to play than existing approaches. Another contribution of our paper is a dataset of the small annotated levels that can be used in future research for learning models for evaluating machine-generated content.

Social Media have been recognised as supportive tools in education for creating benefits that supplement students’ collaboration, class interactions, as well as communication between instructors and students. Active informal interaction and feedback between instructors and students outside class belong to the main reasons behind social media pedagogy. Despite the prevalence of traditional email methods of providing feedback to students, the literature shows that they do not check their emails as frequently as they check their social media accounts. In this paper we present the automatic generation of feedback messages and tweets with context-free grammars (CFG). Our system takes a class list of students and their mark sheets and automatically composes Twitter tweets concerning statistical ‘fun facts’ about programming problems, exercises, class performances, as well as private messages about individual student performances. A survey with 116 participating students showed that the majority of them would like to receive such notifications on social media rather than emails. Lecturers found our system promising, too.

Aesthetic patterns are widely used nowadays, e.g., in jewellery design, carpet design, as textures and patterns on wallpapers, etc. Most of the work during the design stage is carried out by a designer manually. Therefore, it is highly useful to develop methods for aesthetic pattern generation. In this paper, we present methods for generating aesthetic patterns using the dynamics of a discrete dynamical system. The presented methods are based on the use of various iteration processes from fixed point theory (Mann, S, Noor, etc.) and the application of an affine combination of these iterations. Moreover, we propose new convergence tests that enrich the obtained patterns. The proposed methods generate patterns in a procedural way and can be easily implemented on the GPU. The presented examples show that using the proposed methods we are able to obtain a variety of interesting patterns. Moreover, the numerical examples show that the use of the GPU implementation with shaders allows the generation of patterns in real time and the speed-up (compared with a CPU implementation) ranges from about 1000 to 2500 times.

This article discusses the challenges in creating Mutator VR: Vortex, a virtual reality experience based on interaction with semi-autonomous, organically inspired agents. The work allows the immersant to morph between a vast number of procedurallygenerated microworlds, each with its own visual elements, sounds, agent dynamics, and user interactions. We outline two methods used for procedural generation that are based fundamentally on integration of different modalities. Curve-based synthesis is used for simultaneous generation of entity sounds and shape and flow grains are employed to determine both agent dynamics and user interaction with the agents.

In this paper, we present the concept of operator graph scheduling for high performance procedural generation on the graphics processing unit (GPU). The operator graph forms an intermediate representation that describes all possible operations and objects that can arise during a specific procedural generation. While previous methods have focused on parallelizing a specific procedural approach, the operator graph is applicable to all procedural generation methods that can be described by a graph, such as L-systems, shape grammars, or stack based generation methods. Using the operator graph, we show that all partitions of the graph correspond to possible ways of scheduling a procedural generation on the GPU, including the scheduling strategies of previous work. As the space of possible partitions is very large, we describe three search heuristics, aiding an optimizer in finding the fastest valid schedule for any given operator graph. The best partitions found by our optimizer increase performance of 8 to 30x over the previous state of the art in GPU shape grammar and L-system generation.

Copyright held by the owner/author(s). Virtual cities as background scenarios can be used for many 3D video game genres like action. However, the procedural generation of virtual cities for specific video game genres is an on-going research problem. In this paper, we seek to establish a grounding for future work into city generation for specific game genres by exploring how game designers approach existing generation tool-sets. Firstly, we look at the video game city Skara Brae from the party-based role-playing game The Bard’s Tale and try to replicate it using the Wave Function Collapse (WFC) approach to procedural generation. We show in two experimental conditions which parameters for WFC are suitable for replicating the city. Secondly, a pilot user study with eight users shows how they approach creating different video game cities after they preselect a video game genre. The users’ video game level ideas are then discussed, and different output levels are generated using WFC.

Procedural generation of initial states of state-space search problems have applications in human and machine learning as well as in the evaluation of planning systems. In this paper we deal with the task of generating hard and solvable initial states of Sokoban puzzles. We propose hardness metrics based on pattern database heuristics and the use of novelty to improve the exploration of search methods in the task of generating initial states. We then present a system called Beta that uses our hardness metrics and novelty to generate initial states. Experiments show that Beta is able to generate initial states that are harder to solve by a specialized solver than those designed by human experts., Comment: Accepted for publication at IJCAI'19

Pixar films have recently seen drastically rising light counts via procedural generation, resulting in longer render times and slower interactive workflows. Here we present a fully automated, scalable, and error-free light pruning pipeline deployed on Toy Story 4 that reduces final render times by 15--50% in challenging cases, accelerates interactive lighting, and automates a previously manual and error-prone task.

Virtual models' production is of high pertinence in research and business fields such as architecture, archeology, or video games, whose requirements might range between expeditious virtual building generation for extensively populating computer-based synthesized environments and hypothesis testing through digital reconstructions. There are some known approaches to achieve the production/reconstruction of virtual models, namely digital settlements and buildings. Manual modeling requires highly-skilled manpower and a considerable amount of time to achieve the desired digital contents, in a process composed by many stages that are typically repeated over time. Both image-based and range scanning approaches are more suitable for digital preservation of well-conserved structures. However, they usually require trained human resources to prepare field operations and manipulate expensive equipment (e.g., 3D scanners) and advanced software tools (e.g., photogrammetric applications). To tackle the issues presented by previous approaches, a class of cost-effective, efficient, and scarce-data-tolerant techniques/methods, known as procedural modeling, has been developed aiming at the semi- or fully-automatic production of virtual environments composed of hollow buildings exclusively represented by outer façades or traversable buildings with interiors, either for expeditious generation or reconstruction. Despite the many achievements of the existing procedural modeling approaches, the production of virtual buildings with both interiors and exteriors composed by non-rectangular shapes (convex or concave n-gons) at the floor-plan level is still seldomly addressed. Therefore, a methodology (and respective system) capable of semi-automatically producing ontology-based traversable buildings composed of arbitrarily-shaped floor-plans has been proposed and continuously developed, and is under analysis in this paper, along with its contributions towards the accomplishment of other virtual reality (VR) and augmented reality (AR) projects/works oriented to digital applications for cultural heritage. Recent roof production-related enhancements resorting to the well-established straight skeleton approach are also addressed, as well as forthcoming challenges. The aim is to consolidate this procedural modeling methodology as a valuable computer graphics work and discuss its future~directions., info:eu-repo/semantics/publishedVersion

Creative content requires a lot of human resources. Computational creativity gets more attention as computational resources are getting fast enough to quickly create automated content with enough precision and similarity to human-created digital assets. Paper explores terrain generation methods and proposes a different solution to generate mountains. A landscape is created using voxel-based cubes and the base map is modified using generation agents. Vertical points are extended and filled using arithmetic operations between arrays for each vertical point. Height normalization is applied to remove rare mountain elevation layers.

Procedural Content Generation has a focus on the development of digital games, this leaves out a number of interesting domains for a generation of wargames and other board game types. These games are based on limited computational resources, using dice for random numbers and creations via tables. This paper presents a historical look at non-digital methods for PCG application and in particular a taxonomy of methods and locations of their use.

It’s easy to think of procedural generation as a process that occurs digitally, mediated by an algorithm that displays the results on a screen, and this book is filled with examples of methods to create dynamic, rich procedurally generated digital content. I find that one of the richest tools for procedural storytelling is not digital at all but analogue and has existed in one form or another for centuries. That method is the tarot.

Procedural generation in virtual reality (VR) has been used to adapt the virtual world to various indoor environments, fitting different geometries and interiors with virtual environments. However, such applications require that the physical environment be known or pre-scanned prior to use to then generate the corresponding virtual scene, thus restricting the virtual experience to a controlled space. In this paper, we present VRoamer, which enables users to walk unseen physical spaces for which VRoamer procedurally generates a virtual scene on-the-fly. Scaling to the size of office buildings, VRoamer extracts walkable areas and detects physical obstacles in real time, instantiates pre-authored virtual rooms if their sizes fit physically walkable areas or otherwise generates virtual corridors and doors that lead to undiscovered physical areas. The use of these virtual structures allows VRoamer to (1) temporarily block users' passage, thus slowing them down while increasing VRoamer's insight into newly discovered physical areas, (2) prevent users from seeing changes beyond the current virtual scene, and (3) obfuscate the appearance of physical environments. VRoamer animates virtual objects to reflect dynamically discovered changes of the physical environment, such as people walking by or obstacles that become apparent. In our proof-of-concept study, participants were able to walk long distances through a procedurally generated dungeon experience and reported high levels of immersion.

Narrative puzzles involve exploration, logical thinking and progressing a story. This paper presents a narrative design innovation in the form of a system for the procedural generation of such puzzles for use in story-rich games or games with large open worlds. The approach uses an extended type of context-free grammar as the basis for both the generation algorithm and the puzzle solving. Each designer-defined rule in the grammar defines a possible behavior of item types in the game world. Puzzles are generated at runtime on a per area basis, through recursive generation of inputs for outputs. Given a valid grammar, the system guarantees that its puzzles are solvable.

Virtual museums are becoming increasingly popular, especially thanks to the recent spread of low-cost immersive technologies enabling a richer technology-based cultural offer. However, creating a virtual museum commonly requires a lot of effort, especially if a certain visual quality is required.

The present research proposes two procedural content generation approaches for missions and play space in a game with dungeons, and a game prototype developed as a proof of concept for the feasibility of the algorithm and as a test framework for user-based experiments. The first approach will define missions by generating dungeon maps together with locked doors and keys through the use of an evolutionary algorithm. The second approach will populate the generated dungeon space by filling the content of dungeon rooms using space-filling curves and cellular automata algorithms. The evolutionary algorithm evolves tree structures encoding information about the dungeon. The goal is to converge the generated dungeons as close as possible to satisfy the set of parameter inputs provided by a game designer. The dungeon holds information about the amount of rooms, the connections between them and their position in a 2D map. There are also relevant semantic information in the content for the generation of narrative, which presents itself by the placement of unique pairs of keys and locks throughout it. Thus, a feasible way to finish the dungeon can be procedurally generated. The content of rooms are generated using space-filling curves algorithms such as Hilbert and Moore curves as well as Conways Game of Life Cellular Automata. Computational results report that the evolutionary algorithm provides dungeons with up to a 100 rooms very close to the desired ones for a range of different parameter inputs. The early validation tests with humans show no statistical difference between levels procedurally generated and those made by humans. Further user-centred validation tests with the game prototype show the algorithm-generated levels are perceived as equally or even more human-made than their human-authored counterparts, as well as funnier and more difficult. Thus, the research aims to generate gameplay elements combining different algorithms for a single solution, which could be easily adapted to a range of different games. O projeto propõe duas abordagens de geração de conteúdo para missões e mapas em um jogo com calabouços, e um protótipo de jogo desenvolvido como prova de conceito da factibilidade do algoritmo e também como plataforma de testes para experimentos com usuários. A primeira abordagem define missões ao gerar mapas de calabouço em conjunto com chaves e portas trancadas através do uso de um algoritmo evolutivo. Já a segunda abordagem irá popular o espaço do calabouço criado ao preencher o conteúdo de suas salas usando algoritmos de curvas de preenchimento de espaço e autômatos celulares. O algoritmo evolutivo evolui uma estrutura em árvore que codifica informações sobre o calabouço. O objetivo é convergir os calabouços gerados para se aproximar ao máximo da configuração de entrada fornecida por um designer de jogos. O calabouço possui informação sobre as salas, como a quantidade das mesmas, as conexões entre elas e suas posições em um mapa 2D. Também contam com informações semânticas relevantes para a geração de narrativa no calabouço, que são o posicionamento de pares únicos de chaves e fechaduras através do calabouço. Portanto, uma maneira factível para o término do mesmo pode ser gerada proceduralmente. O conteúdo das salas é gerado usando curvas de preenchiment de espaço como as de Hilbert e Moore, além do autômato celular do Jogo da Vida de Conway. Resultados computacionais demonstram que o algoritmo evolutivo é capaz de criar calabouços com propriedades muito próximas às desejadas para uma grande variedade de entradas para calabouços com até 100 salas. Resultados preliminares de validação com humanos mostraram não haver diferença estatística entre os níveis gerados proceduralmente daqueles feitos por humanos. Testes posteriores de validação centrados em humanos com o protótipo de jogo mostram que os níveis gerados pelo algoritmo são percebidos como feitos por humanos de maneira semelhante ou até em maior grau do que suas contrapartidas geradas de fato por humanos, assim como são percebidos como mais divertidos e difíceis do que estas. Portanto, esta pesquisa objetiva gerar elementos de jogabilidade combinando diferentes algoritmos em uma única solução, que pode ser facilmente adaptada para uma variedade de jogos diferentes.

Main goal of this paper is to explore in which situations should some procedural algorithm be used to generate a tree model. Each algorithm is modified so as to be able to generate a tree model whose shape resembles the required model. Space colonization algorithm, algorithm using particle flows and algorithm simulating a Lindenmayer system are compared depending on a time needed to generate a tree with similar complexity. The voxelization procedure of the model and its application in this context is explained. Method for generating a tree mesh on a graphics card using Bezier's curves is presented.