35.1-2, BDI Agents: From Theory to Practice

Notes taken from 'BDI Agents: From Theory to Practive' (1995), by Anand S. Rao and Michael P. Georgeff

1, Introduction

... A number of different approaches have emerged as candidates for the study of agent-oriented systems [] One such architecture views the system as a rational agent having certain mental attitudes of Belief, Desire and Intention (BDI), representing, respectively, the information, motivational, and deliberative states of the agent. These mental attitudes determine the system's behaviour and are critical for achieving adequate or optimal performance when deliberation is subject to resource bounds...

2, The System and its Environment

... First [] it is essential that the sytem have information on the state of the environment. But as this cannot necessarily be determined in one sensing action [] it is necessary that there be some component of system state that represents this information and which is updated after each sensing action. We call such a component the system's beliefs... Thus, beliefs can be viewed as the informative component of system state.

Second, it is necessary that the system also have information about the objectives to be accomplished or, more generally, what priorities or payoffs are associated with the various current objectives []... We call this component the system's desires, which can be thought of as representing the motivational state of the system.

... We seem caught on the horns of a dilemma: reconsidering the choice of action at each step is potentially too expensive and the chosen action possibly invalid, whereas unconditional commitment to the chosen course of action can result in the system failing to achieve its objectives. However, assuming that potentially significant changes can be determined instantaneously, it is possible to limit the frequency of reconsideration and thus achieve an appropriate balance between too much reconsideration and not enough []. For this to work, it is necessary to include a component of system state to represent the currently chosen course of action; that is, the output of the most recent call to the selection function. We call this addtional state component the system's intentions. In essence, the intentions of the system capture the deliberative component of the system.