A multi-level level generator

Generating content at multiple levels of abstractionsimultaneously is an open challenge in procedural content generation.Representing and automatically replicating the style ofa human designer is another. This paper addresses both of these challenges through extending a previously devised methodology for pattern-based level generation. This method builds on an analysis of Super Mario Bros levels into three abstraction levels:micro-, meso- and macro-patterns. Micro-patterns are then used as building blocks in a search-based PCG approach that searches for macro-patterns, which are defined as combinations of meso-patterns. Results show that we can successfully generate levels that replicate the macro-patterns of selected input levels, and we argue that this constitutes an approach to automatically analysing and replicating style in level design

An Integrated Framework for AI Assisted Level Design in 2D Platformers

The design of video game levels is a complex and critical task. Levels need to elicit fun and challenge while avoiding frustration at all costs. In this paper, we present a framework to assist designers in the creation of levels for 2D platformers. Our framework provides designers with a toolbox (i) to create 2D platformer levels, (ii) to estimate the difficulty and probability of success of single jump actions (the main mechanics of platformer games), and (iii) a set of metrics to evaluate the difficulty and probability of completion of entire levels. At the end, we present the results of a set of experiments we carried out with human players to validate the metrics included in our framework.Comment: Submitted to the IEEE Game Entertainment and Media Conference 201

TOAD-GAN: Coherent Style Level Generation from a Single Example

In this work, we present TOAD-GAN (Token-based One-shot Arbitrary Dimension Generative Adversarial Network), a novel Procedural Content Generation (PCG) algorithm that generates token-based video game levels. TOAD-GAN follows the SinGAN architecture and can be trained using only one example. We demonstrate its application for Super Mario Bros. levels and are able to generate new levels of similar style in arbitrary sizes. We achieve state-of-the-art results in modeling the patterns of the training level and provide a comparison with different baselines under several metrics. Additionally, we present an extension of the method that allows the user to control the generation process of certain token structures to ensure a coherent global level layout. We provide this tool to the community to spur further research by publishing our source code.Comment: 7 pages, 7 figures. AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE) 202

Online Level Generation in Super Mario Bros via Learning Constructive Primitives

n procedural content generation (PCG), how to assure the quality of procedural games and how to provide effective control for designers are two major challenges. To tackle these issues, this paper exploits the synergy between rule-based and learning-based methods to produce quality yet controllable game segments in Super Mario Bros (SMB), hereinafter named constructive primitives (CPs). Easy-to-design rules are employed for removal of apparently unappealing game segments, and subsequent data-driven quality evaluation function is learned based on designer's annotations to deal with more complicated quality issues. The learned CPs provide not only quality game segments but also an effective control manner at a local level for designers. As a result, a complete quality game level can be generated online by integrating relevant constructive primitives via controllable parameters. Extensive simulation results demonstrate that the proposed approach efficiently generates controllable yet quality game levels in terms of different quality measures

TropeTwist: Trope-based Narrative Structure Generation

Games are complex, multi-faceted systems that share common elements and underlying narratives, such as the conflict between a hero and a big bad enemy or pursuing some goal that requires overcoming challenges. However, identifying and describing these elements together is non-trivial as they might differ in certain properties and how players might encounter the narratives. Likewise, generating narratives also pose difficulties when encoding, interpreting, analyzing, and evaluating them. To address this, we present TropeTwist, a trope-based system that can describe narrative structures in games in a more abstract and generic level, allowing the definition of games' narrative structures and their generation using interconnected tropes, called narrative graphs. To demonstrate the system, we represent the narrative structure of three different games. We use MAP-Elites to generate and evaluate novel quality-diverse narrative graphs encoded as graph grammars, using these three hand-made narrative structures as targets. Both hand-made and generated narrative graphs are evaluated based on their coherence and interestingness, which are improved through evolution.Comment: submitted, 9 page

A computational model for generating visually pleasing video game maps

In this work we introduce a computational model based on theories of graphical design to generate visually pleasing video game maps. We cast the problem of map generation as an optimization problem and prove it to be computationally hard. Then, we propose a heuristic search approach to solve the map generation problem and use it to generate levels of a clone of Super Mario Bros (SMB) called Infinite Mario Bros (IMB). Before evaluating the levels of IMB generated by our system, we perform a detailed study of the approaches commonly used to evaluate the content generated by computer programs. The evaluation used in previous works often relies on computational metrics. While these metrics are important for an initial exploratory evaluation of the content generated, it is not clear whether they are able to capture the player’s perception of the content generated. In this work we compare the insights gained from a user study with IMB levels generated by different systems with the insights gained from analyzing computational metric values. Our results suggest that current computational metrics should not be used in lieu of user studies for evaluating content generated by computer programs. Using the insights gained in our previous experiment, we performed another user study to evaluate the IMB levels generated by our method. The results show the advantage of our method over other approaches in terms of visual aesthetics and enjoyment. Finally, we performed one last user study that showed that our method is able to generate IMB levels with striking similarity to SMB levels created by professional designers.Neste trabalho apresentamos um modelo computacional baseado em teorias de design para gerar mapas de jogos de plataforma visualmente agradáveis. Nós estudamos o problema de geração de mapas como um problema de otimização e provamos que uma versão simplificada do problema é computacionalmente difícil. Em seguida, propomos uma abordagem de busca heurística para resolver o problema de geração de mapas e utilizamos ela para gerar níveis de um clone do Super Mario Bros (SMB), chamado Infinite Mario Bros (IMB). Antes de avaliar os níveis de IMB gerados pelo nosso sistema, realizamos um estudo detalhado das abordagens comumente utilizadas para avaliar o conteúdo gerado por programas de computador. A avaliação utilizada em trabalhos anteriores utiliza apenas métricas computacionais. Embora esses indicadores são importantes para uma avaliação inicial e exploratória do conteúdo gerado, não é claro se são capazes de capturar a percepção do jogador sobre o conteúdo gerado. Neste trabalho, comparamos os conhecimentos adquiridos a partir de um estudo com seres humanos usando níveis de IMB gerados por diferentes sistemas, com os conhecimentos adquiridos a partir de análise dos valores de métricas computacionais. Os nossos resultados sugerem que as m ́etricas computacionais atuais não devem substituir estudos com seres humanos para avaliar o conteúdo gerado por programas de computador. Usando os conhecimentos adquiridos em nosso experimento anterior, foi realizado outro estudo com seres humanos para avaliar os níveis de IMB gerados pelo nosso método. Os resultados mostram a vantagem do nosso método em relação a outras abordagens em termos de estética visual e diversão. Finalmente, foi realizado outro estudo com seres humanos, mostrando que o nosso método é capaz de gerar níveis de IMB semelhantes aos níveis de SMB criados por designers profissionais.Coordenação de Aperfeiçoamento de Pessoal de Nível Superio

Literature review of procedural content generation in puzzle games

This is the third chapter from my Master Thesis (Automatic Game Generation). This chapter will provide a review of the past work on Procedural Content Generation. It highlights different efforts towards generating levels and rules for games. These efforts are grouped according to their similarity and sorted chronologically within each group.N/