摘要
在高层的数据融合中,往往需要能够觉察和预测态势的变化趋势。因为由多个智能代理构成的交互系统,其态势的变化是靠各方的决策活动推动的,所以纯粹概率的或证据的技术对这类预测并不是充分有效的工具。对于这类预测任务,博弈论工具能够对其不确定的态势演变提供更好的判断与识别,而且博弈论还是一个行动规划工具。通过将关联图推理和博弈论相结合,提出了一种新的决策支持模型——Bayesian博弈模型,用于增强对由多个交互的智能代理形成的复杂局势的觉察和预测能力。通过一个实例,说明了决策者的博弈策略对态势评估的影响,并给出了实例的Bayesian博弈模型。提出的模型和方法克服了传统态势评估中忽略主观因素的缺陷,为具有博弈性质的态势评估提供了一种新的方法。
Variation tendency of situation needs to be perceived and predicted in a high level data fusion process. Be- cause variation tendency of situation of a interaction system combined by multi intelligent agent is pushed forward by their respective decision process, pure probability and evidence theory are not satisfying available tools for this type of prediction. For these prediction,game theory can provide preferable decision and recognition, and is a tools of Process Planning. By combining influence diagrams with game theory, we proposed a new architecture--Bayesian Game Model for decision support to enhance capability of the awareness and prediction for a complex situation caused by multi inter- active intelligent agents. Through a case, we explained the effect of the policymakers＇ game strategies on situation as- sessment and gave the case＇s Bayesian game model. The model and method proposed in the paper overcome the disad- vantage of traditional method that neglects subjective factors, and might offer a new way to situation assessment with game feature.
出处
《计算机科学》
CSCD
北大核心
2013年第7期196-200,共5页
Computer Science
基金
国家自然科学基金项目(60673108)资助
关键词
多源信息融合
博弈论
策略组合
混合策略均衡
贝叶斯博弈
Multisource information fusion, Game theory, Strategy profile, Mixed strategy equilibria, Bayesian game
