Capturing player enjoyment in computer games

The current state-of-the-art in intelligent game design using Artificial Intelligence (AI) techniques is mainly focused on generating human-like and intelligent characters. Even though complex opponent behaviors emerge through various machine learning techniques, there is generally no further analysis of whether these behaviors contribute to the satisfaction of the player. The implicit hypothesis motivating this research is that intelligent opponent behaviors enable the player to gain more satisfaction from the game. This hypothesis may well be true; however, since no notion of entertainment or enjoyment is explicitly defined, there is therefore no evidence that a specific opponent behavior generates enjoyable games.peer-reviewe

How to model and augment player satisfaction : a review

This is a review on approaches for modeling satisfaction perceived by users interacting with entertainment systems. Experimental studies with adult and children users of games (screen-based and physical-interactive) are outlined and the most promising approaches for augmenting player satisfaction while the game is played (i.e. in real-time) are discussed.peer-reviewe

Affective games:a multimodal classification system

Affective gaming is a relatively new field of research that exploits human emotions to influence gameplay for an enhanced player experience. Changes in player’s psychology reflect on their behaviour and physiology, hence recognition of such variation is a core element in affective games. Complementary sources of affect offer more reliable recognition, especially in contexts where one modality is partial or unavailable. As a multimodal recognition system, affect-aware games are subject to the practical difficulties met by traditional trained classifiers. In addition, inherited game-related challenges in terms of data collection and performance arise while attempting to sustain an acceptable level of immersion. Most existing scenarios employ sensors that offer limited freedom of movement resulting in less realistic experiences. Recent advances now offer technology that allows players to communicate more freely and naturally with the game, and furthermore, control it without the use of input devices. However, the affective game industry is still in its infancy and definitely needs to catch up with the current life-like level of adaptation provided by graphics and animation

Project:Filter - using applied games to engage secondary schoolchildren with public policy

Applied games present a twenty-first-century method of consuming information for a specific purpose beyond pure entertainment. Objectives such as awareness and engagement are often used as intended outcomes of applied games in alignment with strategic, organizational, or commercial purposes. Applied games were highlighted as an engagement-based outcome to explore noPILLS, a pan-European policy research project which presented policy pointers and suggested methods of interventions for reducing micropollution within the wastewater treatment process. This paper provides an assessment of a video game which was developed for the purpose of public engagement with policy-based research. The video game, Project:Filter, was developed as a means of communicating noPILLS to secondary school children in Scotland as part of a classroom-based activity. Knowledge development and engagement were identified using Interpretative Phenomenological Analysis to evidence topical awareness, depth of understanding, and suggested methods of intervention. Analysis of observations also provided insights into challenges surrounding logistics, pedagogy, social interactions, learning, and gender as contributing factors to the schoolchildren’s experiences of Project:Filter. The intention of this paper is two-fold: firstly, to provide an example of developing video games from policy-based research; and secondly, to suggest methods of phenomenological assessment for identifying play-based engagement

Preliminary studies for capturing entertainment through physiology in physical play

This report presents preliminary physical control experiments for capturing and modeling the affective state of entertainment — that is, whether people are having "fun" — of users of the innovative Play-ware playground, an interactive physical playground. The goal is to con-struct, using representative statistics computed from children's physio-logical hear rate (HR) signals, an estimator of the degree to which games provided by the playground engage the players. For this purpose chil-dren's HR signals, and their expressed preferences of how much "fun" particular game variants are, are obtained from experiments using games implemented on the Playware playground. Neuro-evolution techniques combined with feature set selection methods permit the construction of user models that predict reported entertainment preferences given HR features. These models are expressed as artificial neural networks and are demonstrated and evaluated on two Playware games and the pre-liminary control task requiring physical activity. Results demonstrate that the proposed preliminary control experiment is not an appropriate control for physical activity effects since it may generate HR dynamics rather easy to separate from game-play HR dynamics, and allows one to distinguish entertaining game-play from exercise purely on the artificial basis of the kind of physical activity taking place. Conclusions derived from this study constitute the basis for the design of more appropriate control experiments and user models in future studies.peer-reviewe

Entertainment modeling in physical play through physiology beyond heart-rate

An investigation into capturing the relation of physiology, beyond heart rate recording, to expressed preferences of entertainment in children’s physical gameplay is presented in this paper. An exploratory survey experiment raises the difficulties of isolating elements derived (solely) from heart rate recordings attributed to reported entertainment and a control experiment for surmounting those difficulties is proposed. Then a survey experiment on a larger scale is devised where more physiological signals (Blood Volume Pulse and Skin Conductance) are collected and analyzed. Given effective data collection a set of numerical features is extracted from the child’s physiological state. A preference learning mechanism based on neuro-evolution is used to construct a function of single physiological features that models the players’ notion of ‘fun’ for the games under investigation. Performance of the model is evaluated by the degree to which the preferences predicted by the model match those expressed by the children. Results indicate that there appears to be increased mental/emotional effort in preferred games of children.peer-reviewe

Developing serious games for cultural heritage: a state-of-the-art review

Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result, the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented

Serious Games in Cultural Heritage

Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented

Game and player feature selection for entertainment capture

The authors would like to thank Henrik Jorgensen and all children of Henriette Horlucks and Rosengardskolen Schools, Odense, Denmark that participated in the experiments. The tiles were designed by C. Isaksen from Isaksen Design and parts of their hardware and software implementation were collectively done by A. Derakhshan, F. Hammer, T. Klitbo and J. Nielsen. KOMPAN, Mads Clausen Institute, and Danfoss Universe also participated in the development of the tiles.The notion of constructing a metric of the degree to which a player enjoys a given game has been presented previously. In this paper, we attempt to construct such metric models of children’s ‘fun’ when playing the Bug Smasher game on the Playware platform. First, a set of numerical features derived from a child’s interaction with the Playware hardware is presented. Then the Sequential Forward Selection and the n- Best feature selection algorithms are employed together with a function approximator based on an artificial neural network to construct feature sets and function that model the child’s notion of ‘fun’ for this game. Performance of the model is evaluated by the degree to which the preferences predicted by the model match those expressed by the children in a survey experiment. The results show that an effective model can be constructed using these techniques and that the Sequential Forward Selection method performs better in this task than n-Best. The model reveals differing preferences for game parameters between children who react fast to game events and those who react slowly. The limitations and the use of the methodology as an effective adaptive mechanism to entertainment augmentation are discussed.This work was in part supported by the Danish National Research Council (project no: 274-05-0511).peer-reviewe