Procedural content generation (PCG) can be a useful tool for aiding creativityand efficiency in the process of designing game levels. Mixed-initiative level genera-tion tools where a designer and an algorithm collaborate to iteratively generate gamelevels have been used for this purpose – taking advantage of the combination of com-putational efficiency and human intuition and creativity. However, it can be difficultfor designers to work with tools that do not respond to the common language of games:game design patterns.It has been demonstrated that game design patterns can be integrated into PCGalgorithms, but formally-defined and hierarchically-arranged game design patternshave not yet been used as a means of increasing gameplay-based control in mixed-initiative dungeon generators. We present a method for evolving dungeon rooms usingmulti-level game design patterns in the objective function of a genetic algorithm, aswell as an instantiation of this method in a mixed-initiative dungeon design tool. Ourresults show that we are able to control the frequency and type of design patterns ingenerated rooms using pattern-related input parameters, enabling us to create dungeonrooms containing a wide variety of patterns on different levels of abstraction.Results from a small-scale user study of professional game developers suggest thatthe use of game design patterns in mixed-initiative level design tools can be a promisingway of providing a good starting point when designing a level, as well as offeringmeaningful gameplay related feedback throughout the design process. We also identifychallenges that will need to be faced if game design pattern-based mixed-initiative leveldesign tools are to become a part of the game designer’s toolkit.

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Games get boring when they start repeating themselves and do not offer players new content. Procedural content generation (PCG) is increasingly used to generate this content. PCG-based game design decreases the need to have a human designer or a writer to generate the content. Algorithmic creation of game content can augment the creativity of human designers and this makes it possible small so-called indie teams to create the content for their game without the big resources. In this work, the field of PCG is introduced. Application of PCG is shown through a mobile game implementation. The implementation details of the mobile game Rush Hour will be presented that makes use of Foursquare, Twitter and Mapbox APIs, which eases the content creation using open data as the input of PCG.

Procedural content generation is a technique used to produce a wide range of computer-generated content in many industries today, the video game industry in particular. This study focuses on how procedural content generation can be applied to create emotionally interesting non-player characters and through this, generate narrative snippets that can immerse and interest a reader. The main points examined are how to achieve this using a modular approach to personality and behaviour, how well readers can distinguish whether motivations and interactions are generated by a computer or written by a human, and to what degree a reader can be immersed in a computer-generated narrative. Procedural narrative could help to reduce workload on large projects or lower costs, and is an area in which there is much room for further research. To answer these problems, a literature review of existing techniques for the creation of emotionally interesting non-player characters was conducted and used to design and construct a prototype implementation for generating procedural narrative. The output of this narrative was dressed up to match the style of a human text and A/B testing was conducted utilising a survey in order to evaluate and compare responses to the two texts. Ultimately, the results showed very little difference between the perception of the human-written text and the computer-written text, with the only aspects found lacking in the computer-written text being clarity of emotion and foreshadowing.

In modern times, procedural content generation sees frequent use in video games, producing anything from graphics to maps and quests. This study focuses on how these techniques can be used to produce forest maps for tactical role-playing games, and how this is applied in particular to Starshard, one such game. The main points addressed are how well the forestry growth simulation algorithm previously implemented in Starshard compares to algorithms based on other popular techniques, how to utilise evaluation and optimisation to produce correct and strategically interesting maps without human interference, and whether or not players can easily perceive a difference between procedural maps and maps designed by humans. With high demand for new algorithms to automate content generation in order to help smaller teams of developers and maintain interest in content post release, there is much value in delving further into less frequently explored aspects such as tile-based maps or player perception of procedural content. In order to answer the research problems, a controlled experiment comparing four forestry generation algorithms was performed, in addition to a study of literature to implement evaluation and optimisation algorithms, and a survey to gauge player reactions to the produced maps. Ultimately, the growth simulation proves to be more successful than alternative algorithms in reducing number of errors in maps. In addition, the results of the survey showed that while players are capable of reliably picking out human created maps, their ratings for procedurally generated maps were not much lower than these and they could frequently mistake procedural maps as being produced by humans.

Procedural content generation inom spel refererar till algoritmiskt, procedurellt skapande av digitalt innehåll i syfte att automatisera och minska mängden arbete för designers och grafiker. Ett område procedural content generation används för inom spel är dungeon generering. Målet för detta arbete var att utforska en 2D algoritm som används i spelet TinyKeep för just generering av dungeons och se hur den algoritmen kunde prestera om den modifierades för generering i en 3D rymd. Den modifierade algoritmen utvärderades baserat på attributen variation, justerbarhet, pålitlighet samt tidseffektivitet. Resultatet visade visade att det är möjligt att använda algoritmen i spelet TinyKeep i en 3D-rymd med godtagbart prestationsresultat. Som värst visade den modifierade algoritmen på en viss svaghet angående genereringstid vid en större tom rymd med större antal rum hos en dungeon. För framtida arbete vore det intressant att dela upp av delar av den modifierade algoritmen på separata trådar. / <p>Det finns övrigt digitalt material (t.ex. film-, bild- eller ljudfiler) eller modeller/artefakter tillhörande examensarbetet som ska skickas till arkivet.</p>

Procedural Content Generation means the algorithmic creation of game content with limited or indirect user input. This technique is currently widespread in the game industry. However, its effects when applied to elements that do not engage directly with the player, also known as Game Bits, require more research. This paper focuses on how players experience a game when these Game Bits are procedurally generated, and how this alters their will to continue playing the game. By developing and using a 2DRogue like game to perform a qualitative study with eight participants, this dissertation shows an indication that procedurally generating Game Bits does not alter how the players experience a game or their desire to replay it.

Background. Virtual Reality is a growing sector that provide the most immersive gaming experiences, especially when the locomotion technique natural walking is used. However, it is always limited by the physical play space available for the user. Introducing Impossible Spaces, also called Overlapping Maps, which when combined with Procedural Content Generation based on the users play space could maximize the experience. Objectives. The aim of this thesis is to implement a potential solution for procedurally generated impossible spaces that are sized according to the VR users playspace. Ultimately testing how the Execution Time is affected when subjecting the implementation to different sized play areas and number of maps to overlap. In addition to this, the thesis will examine the play space setup of various experiencedVR users. Methods. The three core algorithms of the implementation - Grid and Maze generation, as well as Portal placement - are evaluated in terms of execution time. A questionnaire was created for gathering data on VR users and their play space setup. Results. Questionnaire gathered 45 results in total. A majority had access to a play space area of 2-5 square meters. The VR users’ experience affected the size ofthe play space. The execution time for the core algorithms showed promising resultsin terms of execution time. Conclusions. Since most VR users do not have a large play space and the proposed solution performed well, it could be used to enhance the VR experience.

If you want procedurally generated content in your games, you often have to rely on your own ability to develop the desired tools. This can be limiting for newer game developers, leading to certain types of gameplay not being considered when designing games. One instance of this problem regards procedurally generated planets, a rather uncommon type of game world, with a lack of tools online to create your own. To improve upon the issue, this paper sets out to explore how a tool can be developed to supply game developers with worlds in the form of planets. This resulted in Planet Designer, a Unity tool for quickly generating diverse planets with the potential to be used in a variety of game concepts. The tool utilizes layers of manipulated noise to generate wide ranges of terrain, which can be populated with trees, bushes, stones, etc. using a brush. By playing around with the terrain and ocean shaders, the user can give each planet a unique aesthetic through different colors, textures, and thresholds. The paper features an extensive description of how the tool’s features were implemented, and how the tool was evaluated, as well as a discussion about why the tool is considered a valid solution to the problem.

1 Maxim Gumin's Wave Function Collapse (WFC) algorithm is an example-driven image generation algorithm emerging from the craft of procedural content generation. The intended use of the algorithm is to generate new images in the style of given examples by ensuring local similarity. Our work aims to generalize the original work to make the algorithm applicable in other domains. Furthermore, we aim to apply it in a more difficult task of village generation in the 3D sandbox video game Minecraft. We will create a generic WFC library and a Minecraft mod, which will allow for structure generation using WFC. We hope that our WFC library will be beneficial to anyone exploring WFC and its applications in the Kotlin language and that our Minecraft showcase reveals some of the benefits and limits of the algorithm in complex problems.