Adaptive Multi-agent System Based on Wasp-Like Behaviour for the Virtual Learning Game Sotirios

• Published in: Large-Scale Scientific Computing pp. 416 - 424
• Main Authors: Simian, Dana, Bota, Florentin
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing
• Series: Lecture Notes in Computer Science
• ISBN: 3319734407; 9783319734408
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-73441-5_45

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.