Interactive evolution is explored and applied for the automatic generation of 8-bit sound effects (SFX). Procedurally generating a type of content can result in greater accessibility, cut development costs, and more. However, a natural problem that follows this approach is user fatigue. An 8-bit SFX generator is developed, tested, and then evaluated to understand its capabilities, usability, and effectiveness of several applicable solutions for reducing user fatigue. Results indicate that the software is intuitive to learn and use while providing a decent variety to the generated content with a probable feeling of progression. The implemented solutions for abating user fatigue show promise towards making the software practically viable. However, there are still areas in the developed artifact that suggest for further study.

This thesis explores the possibility of combining a noise-based terrain generator with a multi-agent system-based citygenerator for use in overworld map generation for games.The resulting artifact is a generator capable of creating awide variety of landscapes and populating them with citiesthat take advantage of available space and resources. Thegenerated noise is used as a height map which is colorizedto form the basis of the terrain. City agents traverse the space, looking for an optimal place to settle within their view. Once they find their final position, each city creates a number of building agents based on the nearby resources. The city agents take each other and the terrain into account when deciding where the buildings shall be placed. Then, road agents connectfirst the houses, then the cities together. Lastly, points ofinterests such as dungeons, bandit camps and wizard towers are placed, their final positions determined in a similar fashion to the city agents. The analysis of the results indicate that the generator is capable of producing novel terrain, and cities that adapt somewhat well to their surroundings, but offer little variety in existing features from map to map. In addition, more control is necessary to implement the artifact into adevelopment workflow. Respondents rated the maps produced by the generator lower than a map from an existing game ,converted into a similar format, and on a similar level as another map, also from an existing game.

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 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.

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.

Denna studie undersöker olika designval inom datorspel för att skapa intressanta och varierade nivåer som kan tilltala både erfarna spelare och nybörjare inom en av de populäraste fritidsaktiviterna i världen. Att designa en nivå i ett spel är en tidskrävande process, och ett sätt att korta ner på detta arbete är att låta en dator skapa nivåer efter specifika instruktioner, genom en process som kallas för procedurell generering. Målet med denna studie är att ta reda på vilka designval som behöver tas i åtanke för att skapa program för att procedurellt generera nivåer i spel som är anpassade efter en specifik målgrupp. Studiens forskningsfråga lyder: Vilka element krävs i ett 2D-plattformsspel för att spelare skall tycka om spelet? Samt vilka undersökta PCG-algoritmer och parameterinställningar lämpar sig för att skapa ett spel som uppfyller dessa önskemål? För att göra detta utvecklades ett datorspel som använde sig av olika former av procedurell generering. Respondenter från olika målgrupper utformade efter deras spelvanor intervjuades för att ta reda på vilka aspekter personer från varje grupp letade efter i ett datorspel, och det egenutvecklade spelet utformades efter respondenternas svar. Efter detta så fick ett större antal informanter testa spelet och svara på enkätfrågor som sedan sammanställdes och analyserades för att ta reda på vilka aspekter av spelets genererade nivåer som informanterna från varje målgrupp tyckte att datorn hade lyckats med. En del av de resultat vi fått från studien var bland annat att folk som spelar ofta blir mer motiverade av ett poängsystem än folk som spelar mer sällan, samt att alla målgrupper tyckte om en stor variation mellan nivåerna. / This study examines different design choices within computer games to create interesting and varied levels that can appeal to both seasoned gamers and newcomers in one of the most popular hobbies in the world. Designing a level is a time-consuming process, and a way to shorten this work is to let a computer create the levels based on specific instructions, through a process called procedural generation. The goal of this study is to find out what design choices that needs to be taken into account in order to create programs to procedurally generate levels in games that are tailored for a specific target audience. The research question of this study is: Which elements are required in a 2D-platforming game in order for players to enjoy it? And which of the examined PCG-algorithms and parameter settings are suitable for creating a game that fulfils these requirements? In order to do this, a computer game was developed which used various forms of procedural generation. Respondents from target audiences based on their gaming habits were interviewed in order to find out what aspects people from each group looked for in a video game, and the in-house developed computer game was designed based on the respondents’ answers. After this a larger number of people tested the game and answered a survey, which was later compiled and analysed to find out which aspects of the games generated levels that the players from each target audience felt that the computer had been successful in. A part of the results that we found in this study are among other thing that people who play games more often are more motivated by a score system than other players who play less. And that all target audiences prefer varied level design.

Context. Procedural content generation (PCG) refers to algorithmical creation of game content (e.g. levels, maps, characters). Since PCG generators are able to produce huge amounts of game content, it becomes impractical for humans to evaluate them manually. Thus it is desirable to automate the process of evaluation. Objectives. This work presents an automatic method for evaluation of procedural level generators for 2D platform games. The method was used for comparative evaluation of four procedural level generators developed within the research community. Methods. The evaluation method relies on simulation of the human player's behaviour in a 2D platform game environment. It is made up of three components: (1) a 2D platform game Infinite Mario Bros with levels generated by the compared generators, (2) a human-like bot and (3) quantitative models of player experience. The bot plays the levels and collects the data which are input to the models. The generators are evaluated based on the values output by the models. A method based on the simple moving average (SMA) is suggested for testing if the number of performed simulations is sufficient. Results. The bot played all 6000 evaluated levels in less than ten minutes. The method based on the SMA showed that the number of simulations was sufficiently large. Conclusions. It has been shown that the automatic method is much more efficient than the traditional evaluation made by humans while being consistent with human assessments.

Spel idag kräver en enorm mängd arbetstimmar för att skapas, därför behövs alltid sätt att spara tid och automatisera processer. Algoritmer för polygoniseringen av skalärfält, som Marching Cubes, har under de senaste åren blivit ett allt vanligare tillvägagångssätt för att automatiskt generera terräng. Scenkomplexiteten och kraven för visuell kvalitet i dagens spel ökar ständigt. Därmed kommer också kravet för prestandaeffektiva renderingsmetoder. Deferred rendering är en renderingsmetod som kan hantera scener med stora mängder ljuskällor och hög scenkomplexitet samtidigt. För att undersöka integreringen mellan procedurellt skapad terräng och en deferred rendering pipeline, skapades en applikation i DirectX 11 för att undersöka implementeringen och potentiella optimeringar av denna integration. / Detta projekt handlar om slumpmässig procedurell skapning av digital terräng för bruk inom datorspel, och hur man i denna kontext kan ta nytta av en grafikmotor som använder renderingstekniken deferred rendering. / Carl Engström can be reached at: Phone: 076-102 86 00 Mail: Lemmibl@gmail.com Felix Nawrin Oxing can be reached at: Mail: felix@nawrin-oxing.se

Procedural content generation for video games (PCGG) has seen a steep increase in the past decade, aiming to foster emergent gameplay as well as to address the challenge of producing large amounts of engaging content quickly. Most work in PCGG has been focused on generating art and assets such as levels, textures, and models, or on narrative design to generate storylines and progression paths. Given the difficulty of generating harmonically pleasing and interesting music, procedural music generation for games (PMGG) has not seen as much attention during this time. Music in video games is essential for establishing developers' intended mood and environment. Given the deficit of PMGG content, this paper aims to address the demand for high-quality PMGG. This paper describes the system developed to solve this problem, which generates thematic music for non-player characters (NPCs) based on developer-defined attributes in real time and responds to the dynamic relationship between the player and target NPC. The system was evaluated by means of user study: participants confront four NPC bosses each with their own uniquely generated dynamic track based on their varying attributes in relation to the player's. The survey gathered information on the perceived quality, dynamism, and helpfulness to gameplay of the generated music. Results showed that the generated music was generally pleasing and harmonious, and that while players could not detect the details of how, they were able to detect a general relationship between themselves and the NPCs as reflected by the music.

This paper investigates the effectiveness of expressive range and controllability for 2-dimensional tile-based procedural content generation. Procedural content generation (PCG) is the automation of content, often in games, and tile-based PCG is when the generated content is constrained to a grid structure. Mixed-initiative PCG, which is the integration of user control into PCG, has been researched previously for tile-based PCG but the implementations have been limited by lack of breadth and user control over the algorithm. As a result, the expressive ranges and controllabilities of their algorithm have not been comprehensive, and in turn, the concepts of expressive range and controllability not thoroughly scrutinized. For the purpose of examining the concepts of expressive range and controllability, an implementation of declarative modelling, named Mixed-initiative Tile-based Designer (MTD), is made. The MTD combines the mission and shape grammar algorithm proposed by Dormans’ and the level generation system in Spelunky. Nine sets of input parameters, scenarios, are tested, each with 2000 levels generated. For each scenario, the expressive range of its output is examined using the standard evaluation metrics linearity and leniency. The results of the data sampling indicated that an analysis based on expressive range needs to be supported by additional analyses for the insights drawn to be more general. In particular, expressive range needs to be complemented by manual inspection, and linearity when applied to sufficiently complex levels needs to be complemented by additional evaluation metrics. On the other hand, controllability was found to have more significant limitations in its current form because of the normalization of the data that goes into the expressive range. One solution is instead to visualize the raw data of the expressive range and make liberal use of manual inspection. As a secondary study, the feasibility of implementing declarative modelling into 2-dimensional tile-based PCG is investigated through analyzing the MTD. In particular, the MTD’s user interface, procedural output and controllability is examined to determine whether declarative modelling is feasible for 2-dimensional tile-based PCG. / Denna artikel undersöker effektiviteten av uttrycksomfång och kontrollerbarhet för generering av 2-dimensionell rut-baserad procedurinnehåll. Procedurell innehållsgenerering (PCG) är automatisering av innehåll, ofta i spel, och rut-based PCG är när det genererade innehållet är begränsat till en rutnätsstruktur. Blandinitiativ PCG, som är integrationen av användarkontroll i PCG, har undersökts tidigare för rut-baserad PCG men implementeringarna har begränsats av brist på bredd och användarkontroll över algoritmen. Som ett resultat har uttrycksomfången och kontrollerbarheten av deras algoritm inte varit heltäckande, och i sin tur har begreppen uttrycksfullt omfång och kontrollerbarhet inte granskats noggrant. I syfte att undersöka begreppen uttrycksomfång och kontrollerbarhet görs en implementering av deklarativ modellering, benämnd Mixed-initiative Tile-based Designer (MTD). MTD:n kombinerar uppdrags-och formgrammatikalgoritmen som föreslagits av Dormans och nivågenereringssystemet i Spelunky. Nio uppsättningar ingångsparametrar, scenarier, testas, var och en med 2000 genererade nivåer. För varje scenario undersöks det uttrycksomfånget för dess utdata med hjälp av standardutvärderingsmåtten linjäritet och svårighet. Resultaten indikerade att en analys baserad på uttrycksomfång måste stödjas av ytterligare analyser för att insikterna ska bli mer generella. Speciellt måste uttrycksomfång kompletteras med manuell inspektion, och linjäritet när den tillämpas på tillräckligt komplexa nivåer måste kompletteras med ytterligare utvärderingsmått. Å andra sidan visade sig kontrollerbarhet ha mer betydande begränsningar i sin nuvarande form på grund av normaliseringen av data som går in i uttrycksomfånget. En lösning är istället att visualisera rådata från uttrycksomfånget och använda sig av manuell inspektion. Som en sekundär studie undersöks möjligheten att implementera deklarativ modellering i 2- dimensionell rut-baserad PCG genom att analysera MTD. I synnerhet undersöks MTD:s användargränssnitt, procedurutdata och kontrollerbarhet för att avgöra om deklarativ modellering är genomförbar för 2-dimensionell rut-baserad PCG.