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Abstract: "With the increasing potential for gaming hardware and peripherals to support biometrics, their application within the games industry for software and design should be considered. This pa per assesses the ability to use a form of biometric measurement, heart rate, in real - time to improve the challenge and enjoyment of a game by catering it to individuals of varying ability . While the findings of this study are valuable to game developers in terested in providing additional dimensions to gameplay and testing, they may also be useful for those researching medical or the rapeutic applications for games . The results suggest that although the tested game was inherently challenging and enjoyable, t he adaptive affective gameplay was not altering the game enough to induce strong physiological or emotional responses from participants. Biofeedback games lend themselves to medical applications, but adaptive affective games can be used to respond sympathe tically to the player without requiring direct control of physiological responses as a form of input."

Abstract: "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."

Abstract: "Herein is proposed the creation of an Application Program- ming Interface (API) for the Unity 3 and 4 video game de- velopment engine that not only reads behavioral measures from traditional video game input devices (such as if there has been an increase in mouse movements and clicks) but also takes into account physiological measures from biomet- ric devices (such as an increase in respiratory rate). The API parses these inputs based on study results that correlated player performance and engagement with physio- logical signs across several dierent game genres. Through the use of several rudimentary machine learning algorithms, raw physiological data is transformed into data relevant to a developer, including player engagement. The results of these calculations allow a game designer to have powerful tools for detecting when players experience certain emotions, and al- low for the design of aective games. Furthermore, the API also exposes the raw data to de- velopers wishing to propose and utilize their own learning algorithms, to allow for a rich development environment for developers of all skill levels. These development tools will enrich the game experience for the player, as well as prepare designers for the use of the next wave of non-traditional in- put hardware. This report serves to illustrate the current status of the API. A brief overview of the signicance of galvonic skin re- sponse (GSR), heart rate (HR), and respiratory rate (RR) in detecting player performance and engagement will be fol- lowed by a discussion of the API itself and the design choices therein."

Abstract: "In this paper, we describe a methodology for capturing player experience while interacting with a game and we present a data-driven approach for modeling this interaction. We believe the best way to adapt games to a specic player is to use quantitative models of player ex- perience derived from the in-game interaction. Therefore, we rely on crowd-sourced data collected about game context, players behavior and players self-reports of dierent aective states. Based on this informa- tion, we construct estimators of player experience using neuroevolution- ary preference learning. We present the experimental setup and the re- sults obtained from a recent case study where accurate estimators were constructed based on information collected from players playing a rst- person shooter game. The framework presented is part of a bigger picture where the generated models are utilized to tailor content generation to particular player's needs and playing characteristics."

"Abstract-Implementations of mobile games have become prevalent industrial technology due to the ubiquitous nature of mobile devices. However, simultaneous-movement multiplayer games - games that a player competes simultaneously with other players - are usually affected by such parameters as latency, type of game architecture and type of communication technology. This paper makes a review of the above parameters, considering the pros and cons of the various techniques used in addressing each parameter. It then goes ahead to propose an enhanced mechanism for dealing with packet delays based on partitioning the game background into grids. The proposed design is implemented and tested using Bluetooth and Wi-Fi communication technologies. The efficiency and effectiveness of the design are also analyzed."