Modeling and analysis of agents' probabilistic behavior by a non-regenerative stochastic Petri net

When interacting and acting in a dynamic multiagent environment, an agent must ask itself what is presently its best course of action given what it now knows about what the environment will be like when it intends to act. It requires some ability to make decision by computing the probability that relevant propositions will hold at a specified point of time. Among the interaction and action, some of them can be characterized by an exponential time distribution, others might not. This paper presents a nonregenerative stochastic Petri net that allows arbitrary time distributions, use it to model and analyze agents' probabilistic behavior.