Agent Belief: Presentation, Propagation, and Optimization

The aim of the article is to show a stochastic approach for both modelling and optimizing the statistical agent belief in a probability model. Two networks are defined: a decision network D of the agent belief state and a utility network U, presenting the utility structure of the agent belief problem. The agent belief is presented via the following three items (B,D,U), where B is a Bayesian network, presenting the probability structure of the agent belief problem. Two propagation algorithms in D and in U are also presented.