Artificial intelligence (AI) in computer games can enhance the player experience by providing more realistic and dynamic interactions with non-player characters and/or the game environment and is, therefore, an essential skill for game development students to acquire. In this paper, we discuss ten active learning prototypes for undergraduate game development students focusing on AI for Games. The prototypes were implemented in the Unity game engine, and each prototype considers a particular technique or set of algorithms. Depending on the prototype, students are required to interact with it on two levels: 1) by running it within the Unity editor, manipulating the respective technique’s parameters, and experimenting and/or playing with the implemented demo or game; or, 2) in addition to the previous level, by actively changing and expanding the provided code to achieve the desired behavior or result. We performed a survey immediately after contact with the prototypes and found that they were easy for the students to manipulate and/or build upon, and most significantly, that they helped students understand the associated techniques and algorithms.

Use of games as a means of rehabilitation therapy is a concept that has been explored extensively in scholarly research. The promise of using game mechanics and gamified systems as a means to motivate rehabilitation clients for therapy has always been the core argument of exploring such concepts. However, the reality is that in different fields of applications these "serious games" are often superficial, constructing gamified systems around a simulated activity, falling short of leveraging the power of agency, choice and narrative. The Village Druid game is a VR game for upper-limb rehabilitation currently under development which is designed around a deeper, or expanded use of games. The game is being developed in collaboration with rehabilitation therapists and undergoing a series of iterative playtests with rehabilitation clients. This paper describes the development goals and design of the Village Druid game together with the prototype used for the first playtest of the game involving rehabilitation clients. This includes the goals for the prototype’s development in how they relate to constraints and goals for the project. The playtest and related semi-structured interviews and focus-groups are described at the level of data collection instruments and research protocol, as well as results. The paper concludes with lessons learned and aspects of developing expanded therapy games that are suggested by the playtest.

Video games are increasingly present and are currently a dominant vehicle not only for entertainment, but also for information. This position has generated a rapid growth and consequent increase in competitiveness in the game development industry, which has required the exploration of new techniques to engage users. Considering the crucial role of emotions in this domain, an increasingly appreciated approach is the integration of psychophysiology in this context. This project is thus included in the field of psychophysiological analysis, framed within the branch of video games, and consists of the study of different actions and how they can influence emotional intensity. To understand the emotional reactions of players, two versions of a horror game in virtual reality were created, which differ in the way users interact with doors along a virtual scenario. The objective of this work is to understand if more intricate interactions can increase the intensity of human bodily reactions. Thus, to observe this potential phenomenon physiological data was acquired: electrodermal activity, electrocardiogram and respiration; in addition to self-reported questionnaires. Results showed that the version that had a more positive global evaluation by the participants was also the one that presented a higher variation in some physiological indicators, such as heart rate and respiratory signal amplitude. Despite this, no significant differences were observed between both versions, indicating that further study is necessary for any in-depth conclusions.

This paper proposes an empirical framework that aims to classify difficulty according to the player’s physiological response. As part of the experimental protocol, a simple puzzle-based Virtual Reality (VR) videogame with three levels of difficulty was developed, each targeting a distinct region of the valence-arousal space. A study involving 32 participants was conducted, during which physiological responses (EDA, ECG, Respiration), were measured alongside emotional ratings, which were self-assessed using the Self-Assessment Manikin (SAM) during gameplay. Statistical analysis of the self-reports verified the effectiveness of the three levels in eliciting different emotions. Furthermore, classification using a Support Vector Machine (SVM) was performed to predict difficulty considering the physiological responses associated with each level. Results report an overall F1-score of 74.05% in detecting the three levels of difficulty, which validates the adopted methodology and encourages further research with a larger dataset.