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

Algoritme Genetika untuk Desain Level Dinamis pada Game Edukasi Kebakaran Hutan

Forest fire is considered a threat with big potential in halting continuous development because of its effects on the environment. Forest fire attracts more and more attention from the local and international governments because it affects both the economy and the environment. Educating the public about forest fire can come in many ways. One of them is video game which is an interactive game with a graphical user interface. Video game is used for developing knowledge, creativity, emotion, intelligence. and moral acts, that is why video game can be used as a means for educating about forest fire. In the process of developing game, the level design is one of the important factors in determining the quality of a game. This research is using genetic algorithm as a procedural content generation method in designing a level for forest fire education game. Genetic algorithm produced optimal level design from many iterations by choosing the best candidate.Kebakaran hutan dianggap sebagai ancaman yang memiliki potensi besar dalam menghambat pembangunan yang berkelanjutan karena efeknya langsung bagi ekosistem. Kebakaran hutan semakin menarik perhatian dari pihak lokal maupun internasional karena memiliki dampak terhadap lingkungan dan ekonomi. Sosialisasi kebakaran hutan terhadap masyarakat dapat dilakukan melalui berbagai cara. Video Game adalah permainan interaktif dengan antarmuka pengguna melalui gambar yang dihasilkan oleh piranti video. Game dapat berfungsi untuk menumbuhkan pengetahuan, kreativitas, emosi, kecerdasan dan nilai-nilai sikap, oleh karena itu game dapat digunakan sebagai sarana edukasi kebakaran hutan. Dalam pembuatan game, desain level merupakan salah satu faktor utama yang menentukan kualitas gameplay dari suatu game. Penelitian ini menggunakan algoritma genetika sebagai metode Procedural Content Generation dalam desain level dari game edukasi kebakaran hutan. Metode algoritma genetika dapat menghasilkan bentuk level yang optimal dari hasil iterasi dengan memilih kandidat terbaik

Antagonistic and cooperative AGO2-PUM interactions in regulating mRNAs.

Approximately 1500 RNA-binding proteins (RBPs) profoundly impact mammalian cellular function by controlling distinct sets of transcripts, often using sequence-specific binding to 3' untranslated regions (UTRs) to regulate mRNA stability and translation. Aside from their individual effects, higher-order combinatorial interactions between RBPs on specific mRNAs have been proposed to underpin the regulatory network. To assess the extent of such co-regulatory control, we took a global experimental approach followed by targeted validation to examine interactions between two well-characterized and highly conserved RBPs, Argonaute2 (AGO2) and Pumilio (PUM1 and PUM2). Transcriptome-wide changes in AGO2-mRNA binding upon PUM knockdown were quantified by CLIP-seq, and the presence of PUM binding on the same 3'UTR corresponded with cooperative and antagonistic effects on AGO2 occupancy. In addition, PUM binding sites that overlap with AGO2 showed differential, weakened binding profiles upon abrogation of AGO2 association, indicative of cooperative interactions. In luciferase reporter validation of candidate 3'UTR sites where AGO2 and PUM colocalized, three sites were identified to host antagonistic interactions, where PUM counteracts miRNA-guided repression. Interestingly, the binding sites for the two proteins are too far for potential antagonism due to steric hindrance, suggesting an alternate mechanism. Our data experimentally confirms the combinatorial regulatory model and indicates that the mostly repressive PUM proteins can change their behavior in a context-dependent manner. Overall, the approach underscores the importance of further elucidation of complex interactions between RBPs and their transcriptome-wide extent

Generating Levels That Teach Mechanics

The automatic generation of game tutorials is a challenging AI problem. While it is possible to generate annotations and instructions that explain to the player how the game is played, this paper focuses on generating a gameplay experience that introduces the player to a game mechanic. It evolves small levels for the Mario AI Framework that can only be beaten by an agent that knows how to perform specific actions in the game. It uses variations of a perfect A* agent that are limited in various ways, such as not being able to jump high or see enemies, to test how failing to do certain actions can stop the player from beating the level.Comment: 8 pages, 7 figures, PCG Workshop at FDG 2018, 9th International Workshop on Procedural Content Generation (PCG2018

The challenge of Automatic Level Generation for platform videogames based on Stories and Quests

In this article we bring the concepts of narrativism and ludology to automatic level generation for platform videogames. The initial motivation is to understand how this genre has been used as a storytelling medium. Based on a narrative theory of games, the differences among several titles have been identified. In addition, we propose a set of abstraction layers to describe the content of a quest-based story in the particular context of videogames. Regarding automatic level generation for platform videogames, we observed that the existing approaches are directed to lower abstraction concepts such as avatar movements without a particular context or meaning. This leads us to the challenge of automatically creating more contextualized levels rather than only a set of consistent and playable entertaining tasks. With that in mind, a set of higher level design patterns are presented and their potential usages are envisioned and discussed

Analysis and application of rhythm in the design of 2D platformer levels

Abstract. The video game industry has grown quickly from its humble beginnings to one of the largest entertainment industries in the world. Fuelled by the continuous advancements in technology, the quality and quantity of content in AAA video games continues to rise along with customer expectations. But with the ever-higher ambitions, the development budgets and durations rise with them, making the cycle unsustainable on the long run. Procedural content generation is a technique that has the potential of helping break the cycle. The automatic generation of game content, such as levels, could help game developers reach the desired quantity of content with a fraction of the time and money required. However, commercial applications of procedural content generation so far have been largely limited in scope and lacking in quality, with the more successful cases being found in smaller budget indie games. In this study, the possibility to use the idea of rhythm in guiding procedural level generation towards better quality was studied. Using a design science research approach, the gameplay rhythm of original Super Mario Bros. levels was extracted and used to build a rhythm-based procedural 2D platformer level generator. The nature of the generated levels was investigated by computational metrics, and the quality of them was evaluated by a series of playtests. It was found that the existing platformer levels included an extractable rhythm. The rhythm-based level generator that was built upon the found rhythm data produced levels that were closely on par with the original levels, indicating that rhythm has potential applications in informing how a procedural content generator could create more meaningful and higher quality content. Finally, this experimental approach in incorporating music theory to procedural content generation opens up many interesting new avenues for future research

Automatic level generation for platform videogames using genetic algorithms

In this document we present an investigation on automatically generating levels for platform videogames. Common approaches for this problem are rhythm based, where input patterns are transformed in a valid geometry, and chunk based, where samples are humanly created and automatically assembled like a puzzle. The proposal hereby presented is to explore this challenge with the usage of Genetic Algorithms, facing it as a search problem, in order to achieve higher expressivity and less linearity than in rhythm based approach and without requiring human creation as it happens with the chunk based approach. With simple heuristics the system is able to generate playable levels in a small amount of time (one level is created in less than a minute) and with considerable diversity, as our results show

Staying in the Flow using Procedural Content Generation and Dynamic Difficulty Adjustment

Procedural Content Generation (PCG) and Dynamic Difficulty Adjustment (DDA) have been used separately in games to improve player experience. We explore using PCG and DDA together in a feedback loop to keep a player in the flow zone. The central tenet of this work is a conjecture about how the shape of the performance versus difficulty curve changes at the boundaries of the flow zone. Based on this conjecture, we have developed an algorithm that detects when the player has left the flow zone and appropriately adjusts the difficulty to bring the gameplay back into flow, even as the skill of the player is changing. We developed a game-independent algorithm, implemented our algorithm for the open-source Infinite Mario Bros (IMB) game and conducted a user study that supports the hypothesis that players will enjoy the game more with DDA - PCG algorithm

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