The Adaptive Learning Mechanism Design for Game Agents Real-time Behavior Control

摘要：

In this paper, we present an approach of adaptive learning mechanism for game agents real-time behavior control. This approach mainly focuses on how to generate game agents adaptability in real-time. It is possible to apply our approach in complicated game character interactions by following the framework discussed in this paper. We consider the layered architecture, the behavior pattern and the adaptive mechanism design to be the three key points of our approach. We provide a brief example of how to apply adaptive learning in game agents behavior processing. From this example, we demonstrate that the planning and learning process is fast enough to have 3D model rendered in time.

作者: Yingying She Peter Grogono

作者单位: Department of Computer Science and Software Engineering Faculty of Engineering and Computer Science Concordia University,Montreal,Quebec,Canada

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 792-796

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）