当前位置: X-MOL 学术International Journal of Serious Games › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Interactive Ant Colony Optimization to Support Adaptation in Serious Games
International Journal of Serious Games Pub Date : 2019-09-20 , DOI: 10.17083/ijsg.v6i3.308
Michael Kickmeier-Rust , Andreas Holzinger

The success of serious games usually depends on their capabilities to engage learners and to provide them with personalized gaming and learning experiences. Therefore, it is important to equip a game, as an autonomous computer system, with a certain level of understanding about individual learning trajectories and gaming processes. AI and machine learning technologies increasingly enter the field; these technologies often fail, however, since serious games either pose highly complex problems (combining gaming and learning process) or do not provide the extensive data bases that would be required. An interesting new direction is augmenting the strength of AI technologies with human intuition and human cognition. In the present paper, we investigated performance of the MAXMIN Ant System, a combinatorial optimization algorithm, with and without human interventions to the algorithmic procedure. As a testbed, we used a clone of the Travelling Salesman problem, the Travelling Snakesman game. We found some evidence that human interventions result in superior performance than the algorithm alone. The results are discussed regarding the applicability of this pathfinding algorithm in adaptive games, exemplified by Micro Learning Space adaptation systems.

中文翻译:

交互式蚁群优化以支持严肃游戏中的适应

严肃游戏的成功通常取决于其吸引学习者并为其提供个性化游戏和学习体验的能力。因此,重要的是要使作为自主计算机系统的游戏具有对个体学习轨迹和游戏过程的一定程度的理解。人工智能和机器学习技术越来越多地进入该领域;但是,这些技术通常会失败,因为严重的游戏可能会带来高度复杂的问题(将游戏与学习过程结合在一起),或者无法提供所需的广泛数据库。一个有趣的新方向是通过人类的直觉和人类认知来增强AI技术的实力。在本文中,我们研究了组合优化算法MAXMIN蚂蚁系统的性能,有无人为干预算法过程。作为测试平台,我们使用了Traveling Salesman问题的副本,即Traveling Snakesman游戏。我们发现一些证据表明,人为干预比单独的算法具有更高的性能。讨论了有关此寻路算法在自适应游戏中的适用性的结果,以微学习空间自适应系统为例。
更新日期:2019-09-20
down
wechat
bug