Advances in Artificial Intelligence

In the paper we present a methodology to agents’ programming based on a Mental States Framework (MSF) in which mental states types are defined in terms of basic components as an External Content; criterions to determine unsatisfaction, uncertainty, urgency, insistence, intensity and importance associated to a mental state; laws of causality through which a mental state can produce another; and control mechanisms for provoking, selecting, suspending and canceling the processing of a mental state. Besides the mental states types named Belief, Desire and Intention as usually defined, this framework also includes Expectation and any possible other mental states’ type that may be important when modeling interactions among agents in a more complex society. According to this methodology, the agents’ architectures are defined by selecting a set of mental states as established in this framework. And, in the paper it is shown that the Object Oriented Programming is well suitable and interesting to the implementation of those architectures. Therefore an Agent Oriented Programming is seen as an interaction among mental states and architectures spaces by MSF and the Object Oriented Programming.