Modeling player experience in Super Mario Bros

This paper investigates the relationship between level design parameters of platform games, individual playing characteristics and player experience. The investigated design parameters relate to the placement and sizes of gaps in the level and the existence of direction changes; components of player experience include fun, frustration and challenge. A neural network model that maps between level design parameters, playing behavior characteristics and player reported emotions is trained using evolutionary preference learning and data from 480 platform game sessions. Results show that challenge and frustration can be predicted with a high accuracy (77.77% and 88.66% respectively) via a simple single-neuron model whereas model accuracy for fun (69.18%) suggests the use of more complex non-linear approximators for this emotion. The paper concludes with a discussion on how the obtained models can be utilized to automatically generate game levels which will enhance player experience.peer-reviewe

Feature analysis for modeling game content quality

One promising avenue towards increasing player entertainment for individual game players is to tailor player experience in real-time via automatic game content generation. Modeling the relationship between game content and player preferences or affective states is an important step towards this type of game personalization. In this paper we analyse the relationship between level design parameters of platform games and player experience. We introduce a method to extract the most useful information about game content from short game sessions by investigating the size of game session that yields the highest accuracy in predicting players' preferences, and by defining the smallest game session size for which the model can still predict reported emotion with acceptable accuracy. Neuroevolutionary preference learning is used to approximate the function from game content to reported emotional preferences. The experiments are based on a modified version of the classic Super Mario Bros game. We investigate two types of features extracted from game levels; statistical level design parameters and extracted frequent sequences of level elements. Results indicate that decreasing the size of the feature window lowers prediction accuracy, and that the models built on selected features derived from the whole set of extracted features (combining the two types of features) outperforms other models constructed on partial information about game content.peer-reviewe

Dead fun: uncomfortable interactions in a virtual reality game for coffins

Uncomfortable interactions are a common aspect of daily life, and have been explored in Human-Computer Interaction; yet little is known about uncomfortable gaming experiences. In this paper, we report on the design and preliminary evaluation of a game in which one player is invited to lie down in a coffin. Results of an exploratory user study suggest that the restricted space of the coffin along with its unsettling cultural connotation led to an engaging, thought provoking experience. By combining the previously separately explored dimensions of physical and psychological discomfort, we hope to better understand the effects that such challenges can have on player experience

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

Kepuasan Pemain terhadap Desain Rintangan pada Skenario Game Petualang

Desain rintangan dalam skenario game merupakan salah satu faktor yang dapat mempengaruhi motivasi pemain dalam bermain. Hal tersebut dapat berupa variasi pada jebakan atau jumlah musuh yang ada. Sebuah skenario game dengan desain variasi rintangan dapat membuat pemain frustasi jika terlalu sulit atau menjadi bosan karena terlalu mudah untuk dimainkan. Tujuan dari penelitian ini adalah memodelkan desain rintangan pada skenario game petualang dari hasil evaluasi kepuasan pemain dalam memainkan game tersebut, agar dapat dikembangkan lebih baik. Hasil dari penelitian ini adalah sebuah skenario game petualang dengan model permainan side-scrolling 2D yang telah dipublikasikan. Pengambilan hasil evaluasi dilakukan dengan membuat kuesioner secara online dengan 15 jenis pertanyaan. Dalam penelitian ini hanya dibahas 4 dari 15 pertanyaan dengan penekanan poin pembahasan pada desain rintangan didalam skenario game. Terdapat 104 responden yang telah mengisi kuesioner tersebut dengan hasil dari kepuasan pemain dalam melewati desain rintangan yang ada pada rancangan skenario game. Dari hasil evaluasi ini, kedepannya akan dilakukan perbaikan untuk menghasilkan desain rintangan yang lebih baik agar setiap rintangan yang ada pada skenario game petulalang menjadi lebih menantang

‘It’s a-me, Mario!’ Exploring dynamic changes and similarities in the composition of early Nintendo video game music

As with films, a thoughtfully composed video game soundtrack has the ability to dramatically enhance and elevate the experience for the audience or player. This article explores the potential issues and difficulties of composing for video game systems by studying the sound-producing hardware and music for two popular systems from one manufacturer. By comparing two of Nintendo’s Super Mario titles, which appeared on both 8-bit and 16-bit systems, through an analysis of the technology, audio, visual (audiovisual), music, and gameplay elements, it is shown that the musical composition was affected by the limitations of processing power. The discussion shows how the composer, Koji Kondo, overcame the issues of limited computing power by using layers of repetition while applying various functions of music for film to enhance player immersion. Kondo composed theme music that has become engrained in popular culture and is synonymous with one of Nintendo’s flagship franchises (Greening, 2014). By attempting to understand the method or approach behind the composition for earlier systems, it is possible to investigate and discuss the evolution of video game music while acknowledging and contributing to the study of music for games. A musical analysis of the Castle and Underwater themes on each system allows for a direct comparison of the compositional approach, while an audiovisual analysis reveals the presence of existing cinematic tropes and identifies potential influences on the creation of effective musical soundtracks for video games. Applying audiovisual theory to games will require the use of existing literature from Lissa (1965), Gorbman (1987), Chion (1994) and Tagg (2004), along with the work of Collins (2005; 2007a; 2007b; 2008a; 2008b), which adapts and applies audiovisual analysis to video games

Towards automatic personalized content generation for platform games

In this paper, we show that personalized levels can be automatically generated for platform games. We build on previous work, where models were derived that predicted player experience based on features of level design and on playing styles. These models are constructed using preference learning, based on questionnaires administered to players after playing different levels. The contributions of the current paper are (1) more accurate models based on a much larger data set; (2) a mechanism for adapting level design parameters to given players and playing style; (3) evaluation of this adaptation mechanism using both algorithmic and human players. The results indicate that the adaptation mechanism effectively optimizes level design parameters for particular players.peer-reviewe

Digging deeper into platform game level design : session size and sequential features

A recent trend within computational intelligence and games research is to investigate how to affect video game players’ in-game experience by designing and/or modifying aspects of game content. Analysing the relationship between game content, player behaviour and self-reported affective states constitutes an important step towards understanding game experience and constructing effective game adaptation mechanisms. This papers reports on further refinement of a method to understand this relationship by analysing data collected from players, building models that predict player experience and analysing what features of game and player data predict player affect best. We analyse data from players playing 780 pairs of short game sessions of the platform game Super Mario Bros, investigate the impact of the session size and what part of the level that has the major affect on player experience. Several types of features are explored, including item frequencies and patterns extracted through frequent sequence mining.peer-reviewe