Towards Multiplayer Content Online Adaptation using Player Roles and their Interactions
Key: TAGS17-1
Author: Thomas Tregel, Johannes Alef, Stefan Göbel, Ralf Steinmetz
Date: October 2017
Kind: In proceedings
Publisher: Academic Conferences and Publishing International Limited
Book title: Proceedings of The 11th European Conference on Games Based Learning
Keywords: content adaptation, multiplayer, group modelling, mathematical optimization
Abstract: Many multiplayer games feature distinct classes or roles for the players to choose from. This choice however, is often limited, as specific group compositions are required to overcome given individual challenges. This limitation can be to the detriment of player enjoyment if it prevents them from playing their favourite role. To cater every challenge for every possible group composition is infeasible due to the high amount of possible groups and their respective role interactions. These aspects are particularly relevant in the context of game-based learning, when adapting content to the current group of players. To offer a feasible solution to the problem, this paper examines how player roles and their interactions in relation to game content can be modelled and used in an automatic adaptation algorithm. Properties of different roles and their interactions are integrated as group properties. Parameters representing adaptable parts of the game's content are used to model tasks for the group. A suitable balance between the group's properties and the tasks is achieved when the group can overcome the tasks but is still challenged by them. By modelling the balance between the group's properties and the game content as an optimization problem, it allows for fast and efficient determination of an adaptation for the content that offers a suitable balance for any given group. As interactions between roles rarely change between different content sections the modelling effort for groups per section is relatively low. Additionally, sections mostly use game content with comparable game mechanics. Therefore the largest part of the model only has to be determined once and needs to be modified for small model additions. This paper presents an adaptation algorithm employing a mathematical formalization of role interactions and game content. The algorithm has been implemented in MATLAB and evaluated with three selected optimization algorithms. However, the algorithm's concept is independent of any specific optimization algorithm.
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