北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2019, Vol. 42 ›› Issue (2): 50-56.doi: 10.13190/j.jbupt.2018-202

• 论文 • 上一篇    下一篇

一种基于距离调整的动态影响力地图模型

芦效峰1, 王晓明1, 沙晶2   

  1. 1. 北京邮电大学 网络空间安全学院, 北京 100876;
    2. 公安部第三研究所, 上海 201204
  • 收稿日期:2018-09-05 出版日期:2019-04-28 发布日期:2019-04-09
  • 作者简介:芦效峰(1976-),男,副教授,博士生导师,E-mail:luxf@bupt.edu.cn.
  • 基金资助:
    国家自然科学基金项目(61472046);信息网络安全公安部重点实验室开放课题项目(C17607);北京市科协"金桥工程种子资金"项目;中国计算机学会-绿盟科技鲲鹏基金项目(CCF-NSFOUS2018007)

A Dynamic Influence Map Model Based on Distance Adjustment

LU Xiao-feng1, WANG Xiao-ming1, SHA Jing2   

  1. 1. School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China;
    2. The Third Research Institute of the Ministry of Public Security, Shanghai 201204, China
  • Received:2018-09-05 Online:2019-04-28 Published:2019-04-09

摘要: 传统的影响力地图或者缺乏对动态信息的表示,或者对动态信息的表示不准确,容易导致游戏人工智能(AI)主体做出错误的决策.为了解决影响力地图不易描述动态信息的问题,对影响力地图的传播方式和衰减方式进行了研究,提出了基于距离调整的动态影响力地图模型.根据产生影响对象的运动趋势,对影响传播过程中需要计算的距离进行调整,将运动趋势信息编码于最终的影响力地图中,为游戏AI主体的决策过程提供支持.实验结果表明,相较于传统影响力地图模型,该模型可以有效提高影响力地图对游戏环境动态信息表示的准确程度,从而提高AI主体的性能.

关键词: 影响力地图, 游戏人工智能, 动态信息

Abstract: The traditional influence map either lacks the representation of dynamic information or is inaccurate in the representation, which will easily lead to the wrong decision of the game artificial intelligence subject. In order to solve the problem that influence map was difficult to describe dynamic information, the propagation mode and attenuation mode of influence map were studied, and a dynamic influence map model based on distance adjustment was proposed. According to the movement trend of the objects affected, the distance to be calculated in the process of impact propagation was adjusted The model can encode dynamic information into the influence map so as to support decision making of the game agent. Experiments show that compared with traditional influence map, this model can effectively improve the accuracy of the dynamic information representation in influence map, thus enhance the performance of the game agent.

Key words: influence map, game artificial intelligence, dynamic information

中图分类号: