Model Representing of Multi-agent Interactions Based on Dynamic Bayesian Networks
Xuegang Hu · Jisuanji gongcheng · 2003
Dynamic Bayesian networks(DBNs) are a powerful methodology for representing and computing with uncertain problem of stochastic processes. Actions of two above human are modeled by combining agent technology with Bayesian theory. An approach of decomposition and incorporation is developed to resolve that multi-agent system based on dynamic Bayesian networks is intractable for exact calculations. The approach improves ability of model representing. The mutual cause relationship can be represented by the models.