George Tsatiris

Konstantina Ntretska, Nikos Avrantinis, George Tsatiris et al.

Research has shown that digital game players often feel engagement and rapport with a game hero or character when they can channel their own ambitions and goals through the hero's journey in the game world; in essence, they feel a sense of accomplishment and fulfilment whenever they put the game mechanics to use to help the hero reach a positive ending to the game quests. In the case of cooperative gameplay, rapport also has to do with their perception of their peers' skills, gameplay style and behaviour within the game. In this paper, we describe an experiment to identify whether matching players with different personalities, as characterized by the OCEAN or Big-5 personality model, can influence their player experience with a custom-made, cooperative game.

Markos Naftis, George Tsatiris, Kostas Karpouzis

In video games, players' perception of the game world and related information depends on their or the game designer's choice of a virtual camera model. In this paper, we attempt to answer the research question of whether it is possible to identify which camera model is preferred by, fits and best serves each player depending on where they are in a game world and the kinds of challenges they face. To this end, a special type of video game, combining challenges from different game genres, was designed and developed with Unity; thirty players could choose from four camera models at their disposal, depending on where they were in the game world, and utilize the most suitable one to proceed. Each player's preference of camera model was collected using the data platform Unity Analytics and then analyzed. The analysis of the results showed that players managed to adapt to the logic and requirements of the game challenges by choosing different cameras for each of them, depending on the spatial requirements and the presence of enemies or platforms they should jump across from.

Kostas Karpouzis, George Tsatiris

This chapter outlines the relation between artificial intelligence (AI) / machine learning (ML) algorithms and digital games. This relation is two-fold: on one hand, AI/ML researchers can generate large, in-the-wild datasets of human affective activity, player behaviour (i.e. actions within the game world), commercial behaviour, interaction with graphical user interface elements or messaging with other players, while games can utilise intelligent algorithms to automate testing of game levels, generate content, develop intelligent and responsive non-player characters (NPCs) or predict and respond player behaviour across a wide variety of player cultures. In this work, we discuss some of the most common and widely accepted uses of AI/ML in games and how intelligent systems can benefit from those, elaborating on estimating player experience based on expressivity and performance, and on generating proper and interesting content for a language learning game.

George Tsatiris, Kostas Karpouzis

This paper describes the development needed to support the functional and teaching requirements of iRead, a 4-year EU-funded project which produced an award-winning serious game utilising lexical and syntactical game content. The main functional requirement was that the game should retain different profiles for each student, encapsulating both the respective language model (which language features should be taught/used in the game first, before moving on to more advanced ones) and the user model (mastery level for each feature, as reported by the student's performance in the game). In addition to this, researchers and stakeholders stated additional requirements related to learning objectives and strategies to make the game more interesting and successful; these were implemented as a set of selection rules which take into account not only the mastery level for each feature, but also respect the priorities set by teachers, helping avoid repetition of content and features, and maintaining a balance between new content and revision of already mastered features to give students the sense of progress, while also reinforcing learning.