“Adaptation in Applied Video Games: from Player Modelling to
Dynamic Game Adjustment and Enhanced Playability“
By Prof. Boyan Bontchev, Department of Software Engineering,
Sofia University, Bulgaria
Serious video games are widely applied in education, health, safety and training and, thus, help modern e-society in building efficiently knowledge, problem-solving and soft skills, creativity and conceptual thinking. However, though their proven social and cultural impact, applied games require relatively high production costs and offer lower perceived quality compared to the contemporary entertainment games. One promising solution of this problem is creation of adaptive applied video games, which identify implicitly specifics of each individual player (learner) during the game and use them to adjust dynamically some game tasks and features for fitting best that individual. Therefore, adaptive video games need solid modelling of player competences, emotions and styles, in order to achieve better player experiences and, hence, an enhanced overall playability.
The invited talk discusses modern trends and challenges in recent development and application of adaptive video games. It goes through theoretical behavior player models describing dynamic processes of player behavior and emotions during playing the game, and organizational models of player describing properties, attributes and facets of player’s competences. There are discussed possible interconnections among them with time and model space constrains useful for affect-based game adaptation. The speech presents briefly the key ideas and results of the European project ADAPTIMES (ADAPTIve player-centric serious video gaMES), where measuring player’s performance and playing styles is combined with recognition of player’s emotional states and applied for adapting dynamically features of game mechanics, dynamics and aesthetics in order to improve player’s engagement, immersion, excitement, and challenge.
Boyan Bontchev is Professor at Department of Software Engineering at Sofia University and has PhD degree in Parallel Processing from the Bulgarian Academy of Sciences. He has acted as consultant and industrial project manager at many private entities in Europe. In 2000-2001 he managed design and development team of the Shiver massively multiplayer online role-playing game. Since 2001 he runs as founder and managing director of Bonea Ltd. developing mobile games and Web applications.
Prof. Bontchev has participated in many research and industrial projects, both bulgarians and in the scope of EC FP5/6/7. He was technical lead of the Bulgarian team developing a serious business game within the PRIME (Providing Real Integration in Multi-disciplinary Environments) project and, as well, project coordinator of the ADOPTA project dealing with adaptive e-learning platforms for edutainment and game based learning. He was evaluator at Research Executive Agency at EC for the FP7 PEOPLE program. Dr. Bontchev is author of about 100 scientific publications and runs as invited speaker at European conferences and doctoral schools. Since July 2014 he runs as Marie Curie fellow at Brainstorm Multimedia (Valencia, Spain) and is responsible for developing adaptive educational video games.
“The GOV indicator: Learning from Good Practices of the EU Grundtvig LLP project
By Drs. Mark Verhijde, Interim Programmamanager En Adviseur Stedelijke Ontwikkeling, The Netherlands
In this article we introduce and apply the GOV typology in order to analyze various e-Government tools, websites and interactive methods of the EU-project “Open Government in Europe”. In many ways these so-called ‘Good Practices’ (GP) are state of the art examples of open data, e-government tools and innovative relationships between governments and active citizens in Europe. Rich though the examples may be, comparing and evaluating them is not easy, while learning from them or using a specific example in one’s own situation is quite difficult. The proposed indicator GOV, while allowing for three distinct GOV strata, hugely improves the options for meaningful comparison between Good Practices and learning from them. Furthermore, with the GOV typology we observe a difference between the patterning of Good Practices, mainly found in GOV 1.0 and GOV 2.0 strata, and the subset of selected ‘Best Practices’, which tend to clustering in the GOV 2.0 and GOV 3.0 strata. Thirdly, due to the GOV indicator we have a better understanding of the workings of the Good Practices, especially the options of interaction between given GOV strata. The Dutch GOV 2.0 case “Research on Civic Initiatives, DIY’s & Liability” illustrates such behavior, resulting in additional GOV examples, with clear indications of push and pull strategies due to attitudes of governments and citizens and thus providing a solid argument for interaction.