This paper follows the process of the authors using deep game design as means of expression by making a game that models the authors experience of anger suppression. It will be based on theories of psychology to define what suppressed emotions are. It also includes other game design theories that are different from Deep Games discovered in the books Art of Game Design and Game Design Workshop. The ideas of preproduction are looked at briefly.  Subsequently, the game is tested iteratively through qualitative interviews with the purpose of studying how the players identify the metaphors in the game. The development process is documented through three iterations, where each iteration is broken down into the technical aspect, the metaphors, the results of the playtests, the findings, and then a short discussion. The authors find four aspects on how to apply deep game design, and three different understandings of their metaphors by the players. / Den här avhandlingen följer författarnas process att göra ett deep game som ett sätt att utrycka sig om undertryckt ilska. Den kommer till största del grunda sig på teorier om psykologi för att definiera vad undertryckta känslor är. Avhandlingen innehåller även andra speldesignsteorier som skiljer sig ifrån Deep Games som beskrivs i böckerna Art of Game Design och Game Design Workshop. Idéerna från förproduktionen undersöks kort.  Därefter testas spelet iterativt genom kvalitativa intervjuer med syfte att studera hur spelarna identifierar metaforerna i spelet. Sedan undersöks idéerna som skapades under förproduktionen. Utvecklingsprocessen dokumenteras genom tre iterationer, varje iteration bryts ned till dess tekniska delar, metaforer, resultat av speltest, samt en kort diskussion.   Författarna identifierar fyra aspekter på hur man använder deep game design och att spelarna har tre olika förståelser av deras metaforer.

In this thesis we present two approaches to improve automatic playtesting using player modeling. By modeling various cohorts of players we are able to train Convolutional Neural Network based agents that simulate human gameplay using different strategies directly learnt from real player data. The goal is to use the developed agents to predict useful metrics of newly created game content. We validated our approaches using the game Candy Crush Saga, a non-deterministic match-three puzzle game with a huge search space and more than three thousand levels available. To the best of our knowledge this is the first time that player modeling is applied in a match-three puzzle game. Nevertheless, the presented approaches are general and can be extended to other games as well. The proposed methods are compared to a baseline approach that simulates gameplay using a single strategy learnt from random gameplay data. Results show that by simulating different strategies, our approaches can more accurately predict the level difficulty, measured as the players’ success rate, on new levels. Both the approaches improved the mean absolute error by 13% and the mean squared error by approximately 23% when predicting with linear regression models. Furthermore, the proposed approaches can provide useful insights to better understand the players and the game. / I denna uppsats presenterar vi två tillvägagångssätt för att förbättra automatisk speltestning genom modellering av spelare. Genom att modellera olika grupper av spelare kunde vi träna Convolutional Neural Network-baserade agenter för att simulera mänskligt spelande med hjälp av olika strategier som är lärda direkt från mänsklig spelardata. Målet är att använda de utvecklade agenterna för att förutsäga användbar metrik av nyskapat spelinnehåll. Vi validerade vårt tillvägagångssätt genom Candy Crush Saga, ett icke-deterministiskt 3-matchnings pusselspel med mer än tre tusen nivåer. Detta är första gången som spelarmodellering appliceras på ett 3-matchnings pusselspel. De presenterade tillvägagångssätten är mer generella och kan utökas till andra spel. De föreslagna tillvägagångssätten är jämförda med ett tillvägagångssätt som simulerar spelande genom en strategi som är lärd direkt från slumpmässig mänsklig spelardata. Resultatet visar att vårt tillvägagångssätt, genom simulering av olika strategier är, mer exakt för att förutsäga spelarens svårighet, mätt genom spelarens framgång, på nya nivåer. Båda tillvägagångssätten förbättrade mean absolute error med 13% och mean squared error med ungefär 23%. Dessutom kan de föreslagna tillvägagångssätten ge en användbar insikt för att bättre förstå spelarna och spelet.

Video games can both be described as a form of art and as digital products. Video games therefore allow for rich interactions and are regarded as more emotional than software and more interactive than films. Due to the nature of video games, the term user experience (UX) which is commonly used for traditional digital products could be argued to be insufficient. Instead, player experience (PX) should be used when describing players’ rich experiences with video games. This case study aims to use the video game Coridden to examine what players experience when playing a co-op action RPG game. Also, this study aims to examine what the intended player experiences are for Coridden from the game developers’ point of view. Lastly, by examining both the perceived and intended player experiences, this study examines how the experiences can be aligned and how they can be used as guidelines during the design and development process. This was done by using a theoretical framework consisting of the difference between usability, user experience and player experience, the social aspect of playing, and how player experiences can be used as design guidelines. Players playtested Coridden and participated in focus groups using product reaction cards to express their experiences. A focus group with product reaction cards were also used for the developersof the game. Using a thematic and a document analysis, along with the results from the product reaction cards, the study highlighted that players and developers had several perceived and intended player experiences. Further discussion highlighted that some of the players’ and developers’ perceived and intended experiences align, which could be used as future guidelines in the design and development process of Coridden.

Via the use of applied games design methodologies, based on analytical grounding, this paper examines the possibility of developing a new type of Policy Game, Wicked Games, as Participatory Design method for use when working with multiple stakeholders on Critical, Crucial, Complex and Wicked Problems (Rittel & Webber 1973). This paper approaches this topic from a Games Design Research perspective, to shed new light on the qualities of medium for participatory designers. This paper provides a definition of, design heuristics for, and an example of a Wicked Game as a starting point for further work within the topic, as well as providing an analysis of a Formal Analysis as a methodology for extracting tacit knowledge from games, Distributed Playtests as a means for gathering information to allow rapid iteration within games design.

This study explores the application of principles from game design, and the motivational psychology it is founded upon, to the domain of second language acquisition. A gameful design process based on playtesting andanalysis with design lenses is adapted and used to iteratively design and develop a system for conversation practice with the goal of creating a motivating and engaging experience.The results indicate effectiveness of the process, but generalizing the results would require further research with bigger sample sizes and studies with varied core activities.