This thesis describes the implementation and evaluation of a modular approach for generating 2D side-scroller game levels from a procedurally generated 3D world. Manually generating large amounts of game levels can take considerable amounts of time, and it maybe desirable to automate this process, using procedural content generation. The problem with using procedural content generation is that it is hard to generate coherent game levels. We implement a modular pipeline which, given a set of heightmaps, generates a 3Dworld. From this world, 2D game levels are generated by pathing and extracting terrain features which influence the content in the game levels. The resulting 2D game levels will, using our approach, have a coherent and logical look. The game levels themselves do not contain any interesting gameplay. Instead they rely on a game level designer to add gameplay elements. The resulting modular implementation is considered a success, it proves that it is possible to generate 2D game levels from a procedurally generated 3Dworld, using the features of that world.

I den här uppsatsen presenteras ett nytt sätt att procedurellt generera pseudo-oändligadungeons som kan traverseras i tre dimensioner. För att hålla genereringen koherent bådeunder och mellan spelsessioner utgår genereringen från ett ”seed”. Ett seed garanterar sammainnehåll på samma plats varje gång miljön genereras. Med en metod som är baserad iL-system genererar vi här en maze dungeon med tvådimensionell grammatikexpansion ochvi undersöker sedan hur duglig den är. Vi försöker få svaret på hur avancerade L-system somkrävs för att nå en nivå av variation som känns tillräcklig för en miljö av pseudo-oändligkaraktär. Variationstestet samlar data från ett urval områden i den färdiggenererade dungeonen.Resultaten visar på att den utvecklade metoden i det här projektet fungerar väl förändamålet. / In this paper we present a novel way of procedurally generating pseudo infinite dungeonsthat can be traversed in three dimensions. To ensure consistent generation both duringand between playing sessions the generation is ”seeded”. Seeded generation guarantees thesame content in the same place every time the environment is generated. Using a methodbased in L-systems we generate a maze dungeon with two dimensional grammar expansionand explore its viability. We try to find the needed complexity of the L-system to achievea level of variation that feels adequate for an environment of pseudo infinite character.The variation tests collect data from sample areas in the generated dungeons. The resultsindicate that the method used in this project works well for the intended purpose.

I denna uppsats kommer vi att presentera en modell vars syfte är att generera beteende-mönster för rollfigurer i digitala spel. Spelgenren rollspel (eng. Role-playing games) placerarspelaren i en värld fylld av fantastiska monster och modiga hjältar. I ett sådant spel ärde goda karaktärerna minst lika viktiga som de ondskefulla varelser som spelaren kämparmot. Hur ser livet ut för en spelkaraktär när den inte hjälper spelaren på dess äventyr? Dekanske lever som fiskare på havet eller som bönder ute på fältet. Mer troligt är att de bori en by tillsammans med en massa andra spännande karaktärer. Vi undersöker hur sådanakaraktärers vardag ser ut och tittar på en teknik som används för att skapa deras beteen-demönster, Cyclic Scheduling. Tekniken innebär att utvecklare skapar scheman som styrrollfigurernas beteende. Dessa scheman måste skapas i förväg under spelets utveckling ochkräver i stora spel många arbetstimmar för att utvecklas. Modellen vi presenterar i dennauppsats använder tekniken Smart Terrain för att automatiskt generera beteendemönsteroch kan användas för att minska utvecklingstid. Vi diskuterar hur modellen kan användas iföränderliga spelvärldar där utvecklare inte i förhand vet hur spelens omgivningar kommeratt se ut. / In this thesis we present a model for the generation of behaviour patterns for charactersin digital games. In the genre Role-playing games the player is placed in a world filledwith fantastic monsters and brave heroes. In this kind of game the good characters areas important as the evil creatures the player must fight against. What kind of life doesa game character have when not helping the player on adventures? Maybe they live asfishermen on the sea or as farmers in the fields. More likely they live in villages amongstother exciting game characters. We examine what these characters’ daily routines looks likeand look at a technique used for creating their behaviour patterns, Cyclic Scheduling. Thetechnique is used by developers to create schedules that control the behaviour of charactersin games. These schedules have to be created during the game development process andfor bigger games this consumes a lot of time. The model we presents in this thesis uses thetechnique Smart Terrain to automatically generate behaviour patterns thereby reducingthe development time. We discuss how the model can be used in dynamic game worldswhere the developers are unaware of potential changes in the game world.

I denna uppsats presenteras ett verktyg för att assistera skapandet av spelbanor i dungeon-miljö. Skapandet av sådana banor är ofta resurskrävande under produktionen och har fokus på design. För att behålla designaspekten men underlätta arbetet är verktyget framtaget för att med tillgängliga parametrar producera grottgångar för sådana banor. Vi undersöker med användartester hur verktyget kan användas för att effektivisera en känd metod för att skapa spelbanor, men samtidigt skapa den kvalité som eftertraktas. Med detta avser vi inte bara att ta fram ett effektivt verktyg, utan även att demonstrera en metod för att använda procedurell generering av spelinnehåll för ett nytt ändamål inom speldesign. / In this article a tool for assisting the creation of game levels in a dungeon environment is presented. Creating such game levels often requires a large amount of resources during a game production and has focus on design. To keep the aspect of design but ease work, the tool is created to produce caverns for such game levels with accessible parameters. We examine with user tests how the tool can be used to make an existing method for creation of game levels more effective. But at the same time producing the quality that is coveted. With this we do not only hope to produce an effective tool, but also to demonstrate a method for using procedural generation for a new purpose in game design.

This Master's Thesis was performed at SkyMaker AB in Linköping during the spring of 2024. SkyMaker is a company specializing in CAD automation, and this project explores the integration of Procedural Content Generation (PCG) principles into Computer-Aided Design (CAD) to evaluate their potential benefits for CAD users. The focus of the study is on transitioning from Engineer-to-Order (ETO) to Configure-to-Order (CTO) products. The project has been conducted following a structured research and development process. This included a comprehensive literature review, comparisons of game modelling software, and practical development on the DynaMaker platform. The central aim was to assess the applicability of various PCG techniques in CAD. Concepts were developed and evaluated to determine the feasibility and benefits of integrating PCG principles into CAD software, specifically for designing a colony on Mars. The results highlight the potential of combining CAD with PCG, though at a somewhat simplified and foundational level. Through an iterative process, the project demonstrated the feasibility of PCG in CAD design and its potential benefits. Supported by these findings, the influence of PCG on the shift from ETO to CTO was also presented. The findings and methodologies have been thoroughly documented to support further development in this innovative area.

The risk adjustment model currently used does not adequately compensate insurers for predictable differences in individuals' health care expenditures in the Czech Republic. It then leads to financial inequality in the redistribution of funds to the insurance companies and causes their financial problems. This study introduces a PCG model as another method for risk adjustment and determines to what extent the predictive performance of the model can be improved when applied to Czech data. We analyze 10% of population sample in the Czech Republic in years 2011 and 2012. Our results confirm the appropriateness of the PCG model for the Czech environment. When the PCG variables are added to the demographic model, R2 value of the prediction model increases from 2.03% to 13.87%.

Background. Procedural Content Generation (PCG) in Video Games can be used as a tool for efficiently producing large varieties of new content using less manpower, making it ideal for smaller teams of developers who wants to compete with games made by larger teams. One particular facet of PCG is the generation of mazes. Designers that want their game to feature mazes also need to know how to evaluate their maze-complexity, in order to know which maze fits the difficulty curve best. Objectives. This project aims to investigate the difference in complexity between the maze generation algorithms recursive backtracker (RecBack), Prim’s algorithm (Prims), and recursive division (RecDiv), in terms completion time, when solved using a depth-first-search (DFS) algorithm. In order to understand which parameters affect completion time/complexity, investigate possible connections between completion time, and the distribution of branching paths, distribution of corridors, and length of the path traversed by DFS. Methods. The main methodology was an implementation in the form of a C# application, which randomly generated 100 mazes for each algorithm for five different maze grid resolutions (16x16, 32x32, 64x64, 128x128, 256x256). Each one of the generated mazes was solved using a DFS algorithm, whose traversed nodes, solving path, and completion time was recorded. Additionally, branch distribution and corridor distribution data was gathered for each generated maze. Results. The initial results showed that mazes generated by Prims algorithm had the lowest complexity (shortest completion time), the shortest solving path, the lowest amount of traversed nodes, and the lowest proportion of 2-branches, but the highest proportion of all other branch types. Additionally Prims had the highest proportion of 4-6 length paths, but the lowest proportion of 2 and 3 length paths. Later mazes generated by RecDiv had intermediate complexity, intermediate solving path, intermediate traversed nodes, intermediate proportion of all branch types, and the highest proportion of 2-length paths, but the lowest proportion of 4-6 length paths. Finally mazes generated by RecBack had opposite statistics from Prims: the highest complexity, the longest solving path, the highest amount of traversed nodes, the highest proportion of 2-branches, but lowest proportion of all other branch types, and the highest proportion of 3-length paths, but the lowest of 2-length paths. Conclusions. Prims algorithm had the lowest complexity, RecDiv intermediate complexity, and RecBack the highest complexity. Increased solving path length, traversed nodes, and increased proportions of 2-branches, seem to correlate with increased complexity. However the corridor distribution results are too small and diverse to identify a pattern affecting completion time. However the corridor distribution results are too diverse to make it possible to discern a pattern affecting completion time by just observing the data.

The application of PCG to generate puzzles offers great value since their replayability is severely limited, requiring any game that employs them to produce many different puzzles. In this paper we propose a modified version of the progressive content generation approach to function as a mixed-initiative system, to create puzzles for the novel partially physics-based game \textit{Everyone Must Die}. Thus exploring the adaptability and usefulness of the progressive content generation approach for a unique type of puzzle game. Further the mixed-initiative system is explored in relation to how effectively it can generate puzzles with a specified difficulty, an issue many papers exploring puzzle generation neglect. This is explored by implementing and incorporating a PCG system by extending an existing puzzle editor featured in the game. The analysis is conducted with the help of a user study on the developers of the game by testing qualitative experiences with the system. The promising results are then discussed and concluded with suggestions for future work and improvements to the described system and its used approach.

This thesis explores the procedural generation of 3D buildings from the floor plan all the way to the fa¸cade and building’s details such as doors, windows, and roof. Through this, the study explores several techniques and approaches to create different layers of the building generation pipeline. The focus is on implementing a set of algorithms that, when running sequentially, are able to create complete 3D buildings in a short time (so they can be used in online generation), could be used in any open-world game, and with a limited count of triangles per building. Furthermore, the tool provides a clear and easy-to-use interface for designers in Unity, where they can interact with the multiple parameters of each building layer, giving designers a high degree of controllability. The tool is evaluated using the resulting buildings based on different metrics and how individual changes to different parameter starting from a template affect the output of the generator in terms of the metrics and the resulting building. The result from the analysis show that the polygon mathematics is well suited for generating 3D buildings for games.

This thesis explores the possibilities of creating landscapes through procedural means within the game engine Unreal Engine 5. The aim is to provide a flexible procedural landscape tool that doesn't limit the user and that is compatible with existing systems in the engine. The research questions focuses on comparison to other work regarding landscape generation and generation of procedural roads. The process to achieve this was done through extensive implementation adding modules that both builds upon and adds to the source code. The implementation was divided into five major components, which was noise generation for terrain, biotope interpolation, asset distribution, road generation and a user interface. Perlin noise, utilizing Fractal Brownian Motion were a vital part of generating terrain with varying features. For interpolation a modified version of Lowpass Gaussian filtering was implemented in order to blend biotope edges together. Asset distribution and road generation were implemented in a way that uses pseudo-randomness combined with heuristics. The user interface was done to tie everything together for testing. The results shows potential for assisting in procedural landscape creation with a large amount of freedom in customization. There is however flaws in some aspects, namely the interpolation methods suffer from clear visual artefacts. Whether it is suitable for professional standards remains to be fully proven objectively as the testing in this thesis work was limited.