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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Adaptive Multi-agent System Based on Wasp-Like Behaviour for the Virtual Learning Game Sotirios
verfasst von : Dana Simian, Florentin Bota
Erschienen in: Large-Scale Scientific Computing
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Abstract
The aim of this paper is to propose a model for an adaptive multi-agent system based on wasp-like behaviour for dynamic allocation of puzzles and quests in the virtual learning game SOTIRIOS. This is a digital learning game integrated inside a First Person Shooter designed by the second author of this paper. The learning process is based on many puzzles hidden in the game flow. The multi-agent system is necessary to integrate a multiplayer mode into the game. The agents use wasp task allocation behaviour, combined with a model of wasp dominance hierarchy in order to create a unique multiplayer learning system, where each user has a different learning curve, based on his results. The wasp behaviour is required to create a balanced multiplayer mode and to optimize the results of teams within the game.