An architecture for rational agents interacting with complex environments

Artificial Intelligence encompasses the enterprise of building an intelligent agent. To this purpose, the notions of agency and intelligence need to be precisely defined. Much to our demise, intelligence has proved to be hard to grasp in a formal way. To overcome this, Stuart Russell— among others—propounded rational agency as an alternative characterization for intelligent agency. In his own words [9], “rational agents [. . . ] are agents whose actions make sense from the point of view of the information possessed by the agents and its goals”. Simply put, a rational agent is an agent that does the right thing based on its beliefs [5]. Naturally, the construction of rational agents is by no means an easy assignment; in fact, it is a large and complex endeavor. Software Engineering has a long standing tradition tackling tough projects. As a general norm, proper modularization has provided the key to success in these tasks. Therefore, different agent architectures have been proposed. The agent architecture supplies a separation of concerns, inducing a tentative modularization. However, at the present state of affairs, to build a fully rational agent is rather unattainable; several issues remain overlooked, or just partially addressed (i.e., addressed under too unrealistic assumptions). Rao and Wooldridge [7] underscore the following aspects: