Harry Agius

Developing Knowledge-Based Intelligent Multimedia TutoringSystems Using Semantic Content-Based Modelling

The complex nature of semantic video and audio content has made multimedia difficult to use within the traditional architecture of a knowledge-based intelligent tutoring system (ITS). This paper investigates how multimedia syntax and semantics may be integrated into the confines of the knowledge-based ITS architecture so as to develop a knowledge-based intelligent multimedia tutoring system (IMTS). The paper contributes a semantic content-based model that can be used for this purpose. Multimedia frames (m-frames) are used as the framework by which the syntactic and semantic information is represented within the model. The paper discusses how IMTSs may be developed using the model, and then demonstrates the use of our approach in the development of ARISTOTLE, an IMTS for teaching young children basic zoology.

Exchanging Social Information in Online Social Games

This chapter presents the phenomenon of social games analyzing the key concept of social information (SI), which is the primal material of the game interactions. It introduces first a classification of digital social games existing nowadays, then our understanding of SI and its presence in different games. Further, the chapter elaborates on three study cases (FarmVille, Pet Society, and Starcraft II) of social games in order to provide schemes of how SI is implemented and used in a digital gaming context, including the opportunity to exchange it. A model of SI exchange is introduced and developed at the level of scenarios, communication processes, and most relevant messages. Finally a discussion recaps the results of the authors ?> exploration of SI in the online gaming landscape.

Toward the Adaptive Generation of Bespoke Game Content

In this chapter, we explore methods for automatically generating game content — and games themselves — adapted to individual players, in order to improve their playing experience or achieve a desired effect. This goes beyond notions of mere replayability, and involves modelling player needs to maximise their enjoyment, involvement and interest in the game being played. We identify three main aspects of this process: Generation of new content and rule sets; Measurement of this content and the player; Adaptation of the game to change player experience. This process forms a feedback loop of constant refinement, as games are continually improved while being played. Framed within this methodology, we present an overview of our recent and ongoing research in this area. This is illustrated by a number of case studies that demonstrate these ideas in action over a variety of game types, including: 3D action games, arcade games, platformers, board games, puzzles and open world games. We draw together some of the lessons learned from these projects to comment on the difficulties, the benefits and the potential for personalised gaming via adaptive game design.