As video games continue to become larger, more complex, and more costly to produce, research into methods to make game creation easier and faster becomes more valuable. One such research topic is procedural generation, which allows the computer to assist in the creation of content. This dissertation presents a new algorithm for the generation of Sokoban levels. Sokoban is a grid-based transport puzzle which is computational interesting due to being PSPACE-complete. Beyond just generating levels, the question of whether or not the levels created by this algorithm are interesting to human players is explored. A study was carried out comparing player attention while playing hand made levels versus their attention during procedurally generated levels. An auditory Stroop test was used to measure attention without disrupting play.

I detta kandidatarbete har vi undersökt hur man på bästa sätt kan främja direktmedieringen med hjälp av den visuella designen. Detta utforskades och visualiserades genom ett tredimensionellt pusselspel med fem olika objekt som innehåller olika pussel, där vi har fokuserat på den visuella designen. Som designperspektiv har vi använt ramverket MDA i kombination med core pillars för att hålla oss inom rätt områden i vår designprocess. Några övriga metoder vi använt under projektets gång var: Metod 635, scrumban, moodboards. Resultatet blev genom vår gestaltning en kombination av olika medie- och designval i ett försök att hitta balansen för rätt estetiska känsla. / In this bachelor thesis, we have investigated how to best promote immediacy using visual design. This was explored and visualized through a three-dimensional puzzle game with five different objects containing different puzzles, where we focused on the visual design. As a design perspective, we have used the MDA framework in combination with core pillars to keep us in relevant areas in our design process. Some other methods we used during the project were: Method 635, scrumban, mood boards. The result was, through our design, a combination of different media and design choices in an attempt to find the balance for the right aesthetic feeling.

This study sought a method for influencing people to anthropomorphize nonhuman agents in video games by making them seem unpredictable. This was inspired by Epley et al.’s (2007) Three-factor theory for anthropomorphism with focus on effectance motivation. It was also inspired by the studies done by Waytz et al. (2010) showing that perceived unpredictability about an agent causes people to anthropomorphize it. To see if perceived unpredictability would cause people to anthropomorphize a nonliving object in a video game, two versions of a game was created, one in which an object with seemingly random behavior was described as unpredictable and one in which the objects behavior was explained beforehand. The data gathered from the participants did not show any statistically significant differences between those that played one version and those that played the other. Meaning that in this case perceived unpredictability didn’t influence people to anthropomorphize a video game object.

This study is focused on the challenges in puzzle video games. Based on several previous studies, the researcher created seven different types of challenges in puzzle games. To study the key of challenging levels in puzzle games, three games were chosen, then walkthrough videos of these games were watched and challenges were noted and categorized into different types. The collected data showed that different puzzle games have different challenge types while abstract reasoning is the most common challenge in every puzzle game. The total challenge numbers and pacing in puzzle video games strongly depend on the design intention of the game. And The number of challenge types has no direct connection with difficulty. The category of seven types of challenges and the results of this study may bring reference and inspiration to future studies. It may also shed some light on puzzle game design.

Nöje är en viktig aspekt i spel som spelas för underhållning. För att kontrollera om ett spel är roligt krävs speltestning, men i denna process uppstår det flera nivåer av störvariabler som påverkar tolkningen av resultatet. Det tycks alltså finnas ett behov av objektiva och mätbara variabler i speltestning. Därför ämnade denna studie besvara frågan om vad sambandet mellan antal misslyckanden och upplevt nöje är. I undersökningen bjöds 18 respondenter in för att spela ett pusselspel, som hade konstruerats enligt etablerade designprinciper och med syftet att tydligt visa när spelarna gör felaktiga handlingar som resulterar i misslyckanden. Därefter besvarade de inbjudna respondenterna på en frågeenkät, som utformades enligt Sweetser och Wyeths GameFlow-modell, för att uppskatta deras upplevda nöje. Två potentiella samband kunde uppmärksammas: Pusselspel tycks ha en mängd misslyckanden, ett gyllene intervall, som resulterar i mest nöje, och gradvisa förändringar i antal misslyckanden i nivåer som följer varandra ökar spelarens upplevelse av nöje. / <p>Det finns övrigt digitalt material (t.ex. film-, bild- eller ljudfiler) eller modeller/artefakter tillhörande examensarbetet som ska skickas till arkivet.</p><p>There are other digital material (eg film, image or audio files) or models/artifacts that belongs to the thesis and need to be archived.</p>

Only a decade ago, research was limited regarding enjoyment and player motivation in digital games. The aim of this study was to investigate the effect of a developed story in a mobilepuzzle game. The main research question was if a developed story can affect the motivation to play a mobile puzzle game, and the secondary question was if a developed story can affect players’ overall impression of a mobile puzzle game. The sample size was eight participants (five men, two women, one non-disclosed), who enjoys playing mobile games, and were between 20-28 years old. A semi-controlled field study was performed with a between-group design consisting of experimental group and control group. Participants played freely a mobile puzzle game with a pre-existing or a developed story for a week, then returned for an evaluation interview. Their total playtime was measured with on-screen time trackers and their motivation and overall impression with subjective ratings on a five-level scale, as well as their reasonings to the ratings. The results showed no main difference between the two conditions. However, exploratory analysis found that participants who were interested in a story had lower motivation to continue playing compared to those not interested in a story, possibly due to their player type. This study makes way for future research regarding story and video games, mobile games in particular. In the long run this research could contribute to make mobile games more immersive and enjoying to play for the public. / För bara ett årtionde sen var forskning begränsad kring nöje och spelares motivation i digitala spel. Syftet med studien var att undersöka effekten av en utvecklad berättelse i ett mobiltpusselspel. Den huvudsakliga forskningsfrågan var om en utvecklad berättelse kan påverka motivationen för att spela ett mobilt pusselspel, andra forskningsfrågan var om en utvecklad berättelse kan påverka spelarnas helhetsintryck av ett mobilt pusselspel. Stickprovet bestod av åtta deltagare (fem män, två kvinnor och en som valde att ej ange kön) som gillar att spela mobilspel och som var mellan 20-28 år gamla. En semi-kontrollerad fältstudie genomfördes med en mellangruppsdesign som bestod av experimentgrupp och kontrollgrupp. Deltagarna fick fritt spela ett förbestämt mobilt pusselspel med antingen den existerande eller den utvecklade berättelsen i en vecka, sedan komma tillbaka för en intervju med återkoppling. Deras totala speltid mättes med “on-screen”-tid, deras motivation och helhetsintryck med hjälp av subjektiva skattningar på en skala 1-5, tillsammans med deras resonemang bakom skattningarna. Resultaten visade ingen skillnad mellan de två betingelserna. Den utforskande analysen föreslår dock att deltagare som var intresserad av en berättelse hade lägre motivation att fortsätta spela jämfört med de som inte var intresserade av berättelsen, möjligen på grund av deras speltyp. Studien banar väg för framtida forskning gällande berättelser och spel, specifikt mobilspel. På lång sikt kan den här forskningen bidra till att göra mobilspel som ger mer inlevelse och är roligare att spela för allmänheten.

This study delves into the relationship between Dynamic Game Difficulty Balance and Game User Experience in the context of puzzle games. The aim of this study was to explore the impact of DGDB on user experience in puzzle games, focusing on player engagement, immersion, and the occurrence of a-ha moment. To this end, the researchers conducted a control group experiment and analyzed the results both quantitatively and qualitatively based on participants' objective data during the game and subjective responses in the post-game questionnaire. The findings suggest that DGDB has the potential to increase player engagement and satisfaction, but the impact is modest, as evidenced by higher completion rates and flow channels in puzzle games. We explored the impact of the DGDB system on a-ha moment and the results were mixed. However, it is clear that the relationship between DGDB and puzzles is a delicate one, with players' preferences and perceptions varying.

Na última década diversos algoritmos baseados em busca foram desenvolvidos para a geração de níveis em diferentes tipos de jogos. O espaço de busca para geração de níveis geralmente possui restrições, uma vez que a mecânica de um jogo define regras de factibilidade para os níveis. Em alguns métodos, a avaliação de factibilidade requer uma simulação com um agente inteligente que controla o jogo. Esse processo de avaliação geralmente possui ruído, causado por componentes aleatórios no simulador ou na estratégia do agente. Diversos trabalhos têm utilizado simulação como forma de avaliação de conteúdo, no entanto, nenhum deles discutiu profundamente a presença de ruído neste tipo de abordagem. Assim, esse trabalho apresenta um algoritmo genético capaz de gerar níveis factíveis que são avaliados por um agente inteligente em uma simulação ruidosa. O algoritmo foi aplicado a jogos de quebra-cabeças baseados em física com a mecânica do Angry Birds. Uma representação dos níveis em forma de indivíduos é introduzida, a qual permite que o algoritmo genético os evolua com características diferenciadas. O ruído na função de aptidão é tratado por uma nova abordagem, baseada em uma sistema de cache, que auxilia o algoritmo genético a encontrar boas soluções candidatas. Três conjuntos de experimentos foram realizados para avaliar o algoritmo. O primeiro compara o método de cache proposto com outros métodos de redução de ruído da literatura. O segundo mede a expressividade do algoritmo genético considerando as características estruturais dos níveis gerados. O último avalia os níveis gerados considerando aspectos de design (como dificuldade, imersão e diversão), os quais são medidos por meio de questionários respondidos por jogadores humanos via Internet. Os resultados mostraram que o algoritmo genético foi capaz de gerar níveis distintos que são tão imersíveis quanto níveis produzidos manualmente. Além disso, a abordagem de cache lidou apropriadamente com o ruído nos cálculos de aptidão, permitindo uma correta evolução elitista. / In the last decade several search-based algorithms have been developed for generating levels in different types of games. The search space for level generation is typically constrained once the game mechanics define feasibility rules for the levels. In some methods, evaluating level feasibility requires a simulation with an intelligent agent which plays the game. This evaluation process usually has noise, caused by random components in the simulator or in the agent strategy. Several works have used a simulation for content evaluation, however, none of them have deeply discussed the presence of noise in this kind of approach. Thus, this paper presents a genetic algorithm capable of generating feasible levels that are evaluated by an intelligent agent in a noisy simulation. The algorithm was applied to physics-based puzzle games with the Angry Birds mechanics. A level representation in the form of individuals is introduced, which allows the genetic algorithm to evolve them with distinct characteristics. The fitness function noise is handled by a new approach, based on a cache system, which helps the genetic algorithm finding good candidate solutions. Three sets of experiments were conducted to evaluate the algorithm. The first one compares the proposed cache approach with other noise reduction methods of the literature. The second one measures the expressivity of the genetic algorithm considering the structural characteristics of the levels. The last one evaluates design aspects (such as difficulty, immersion and fun) of the generated levels using questionnaires answered by human players via Internet. Results showed the genetic algorithm was capable of generating distinct levels that are as immersive as levels manually designed. Moreover, the cache approach handled properly the noise in the fitness calculations, allowing a correct elitist evolution.

Na última década diversos algoritmos baseados em busca foram desenvolvidos para a geração de níveis em diferentes tipos de jogos. O espaço de busca para geração de níveis geralmente possui restrições, uma vez que a mecânica de um jogo define regras de factibilidade para os níveis. Em alguns métodos, a avaliação de factibilidade requer uma simulação com um agente inteligente que controla o jogo. Esse processo de avaliação geralmente possui ruído, causado por componentes aleatórios no simulador ou na estratégia do agente. Diversos trabalhos têm utilizado simulação como forma de avaliação de conteúdo, no entanto, nenhum deles discutiu profundamente a presença de ruído neste tipo de abordagem. Assim, esse trabalho apresenta um algoritmo genético capaz de gerar níveis factíveis que são avaliados por um agente inteligente em uma simulação ruidosa. O algoritmo foi aplicado a jogos de quebra-cabeças baseados em física com a mecânica do Angry Birds. Uma representação dos níveis em forma de indivíduos é introduzida, a qual permite que o algoritmo genético os evolua com características diferenciadas. O ruído na função de aptidão é tratado por uma nova abordagem, baseada em uma sistema de cache, que auxilia o algoritmo genético a encontrar boas soluções candidatas. Três conjuntos de experimentos foram realizados para avaliar o algoritmo. O primeiro compara o método de cache proposto com outros métodos de redução de ruído da literatura. O segundo mede a expressividade do algoritmo genético considerando as características estruturais dos níveis gerados. O último avalia os níveis gerados considerando aspectos de design (como dificuldade, imersão e diversão), os quais são medidos por meio de questionários respondidos por jogadores humanos via Internet. Os resultados mostraram que o algoritmo genético foi capaz de gerar níveis distintos que são tão imersíveis quanto níveis produzidos manualmente. Além disso, a abordagem de cache lidou apropriadamente com o ruído nos cálculos de aptidão, permitindo uma correta evolução elitista. / In the last decade several search-based algorithms have been developed for generating levels in different types of games. The search space for level generation is typically constrained once the game mechanics define feasibility rules for the levels. In some methods, evaluating level feasibility requires a simulation with an intelligent agent which plays the game. This evaluation process usually has noise, caused by random components in the simulator or in the agent strategy. Several works have used a simulation for content evaluation, however, none of them have deeply discussed the presence of noise in this kind of approach. Thus, this paper presents a genetic algorithm capable of generating feasible levels that are evaluated by an intelligent agent in a noisy simulation. The algorithm was applied to physics-based puzzle games with the Angry Birds mechanics. A level representation in the form of individuals is introduced, which allows the genetic algorithm to evolve them with distinct characteristics. The fitness function noise is handled by a new approach, based on a cache system, which helps the genetic algorithm finding good candidate solutions. Three sets of experiments were conducted to evaluate the algorithm. The first one compares the proposed cache approach with other noise reduction methods of the literature. The second one measures the expressivity of the genetic algorithm considering the structural characteristics of the levels. The last one evaluates design aspects (such as difficulty, immersion and fun) of the generated levels using questionnaires answered by human players via Internet. Results showed the genetic algorithm was capable of generating distinct levels that are as immersive as levels manually designed. Moreover, the cache approach handled properly the noise in the fitness calculations, allowing a correct elitist evolution.