摘要
交互式动态影响图(I-DIDs)是基于概率图形理论的多智能体动态交互决策的图模型.为缓解该模型状态空间随时间片增加呈指数级增长的趋势,文中基于行为等价的基本思想压缩状态空间,提出构建Epsilon行为等价类的方法:利用有向无环图表示其它Agent可能的信度和行为,把信度在空间上接近的模型聚为一类,实现自顶向下合并行为等价模型.该过程避免求解状态空间中的所有候选模型,节省了存储空间和计算时间.模型实例上的仿真结果显示了该算法的有效性.
Interactive Dynamic Influence Diagrams （I-DIDs）, as graphic models based on probabilistic graphical theory, are proposed to represent, the sequential decision-making problem over multiple time steps in the presence of other interacting agents. The algorithms for solving I-DIDs are haunted by the challenge of an exponentially growing space of candidate models ascribed to other agents over time. In this paper, in order to reduce the candidate model space according the behaviorally equivalent theory, a more efficient way to construct Epsilon behavior equivalence classes is discussed that using belief-behavior graph （BBG）. A method of solving I-DIDs approximately is presented, which avoids solving all candidate models by clustering models with beliefs that are spatially close and selecting a representative one from each cluster. The simulation results show the validity of the improved algorithm.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2011年第4期506-513,共8页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金资助项目(60975052)
关键词
AGENT建模
交互式动态影响图
动态决策
ε-行为等价
信度-行为图
Agent Modeling, Interactive Dynamic Influence Diagrams （ I-DIDs）, Dynamic DecisionMaking, ε-Behavioral Equivalence, Belief-Behavior Graph （BBG）
