Monday, 12 November 2007

35.3-7, BDI Agents: From Theory to Practice

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

3, Decision Trees to Possible Worlds

4, BDI Logics

The above transformation [of Section 3] provides the basis for developing a logical theory for deliberation by agents that is compatible with quantitative decision theory in those cases where we have good estimates for probabilities and payoffs. However, it does not address the case in which we do not have such estimates, nor does it address the dynamic aspects of deliberation, particularly those concerning commitment to previous decisions.

We begin by abstracting the model given above to reduce probabilities and payoffs to dichotomous (0-1) values. That is, we consider propositions to be either believed or not believed, desired or not desired, and intended or not intended, rather than ascribing continuous measures to them. Within such a framework, we first look at the static properties we would want of BDI systems and next their dynamic properties...

Static Constraints: The static relationships among the belief-, desire-, and intention-accessible worlds can be examined along two different dimensions, one with respect to the sets of possible worlds and the other with respect to the structure of the possible worlds...

Dynamic Constraints: As discussed earlier, an important aspect of a BDI architecture is the notion of commitment to previous decisions. A commitment embodies the balance between the reactivity and goal-directedness of an agent-oriented system. In a continuously changing environment, commitment lends a certan sense of stability to the reasoning process of an agent. This results in savings in computational effort and hence better overall performance.

A commitment usually has two parts to it: one is the condition that the agent is committed to maintain, called the commitment condition, and the second is the condition under which the agent gives up the commitment, called the termination condition. As the agent has no direct control over its beliefs and desires, there is no way that it can adopt or effectively realize a commitment strategy over these attitudes. Thus we restrict the commitment condition to intentions...

5, Abstract Architecture

6, Applications

7, Comparison and Conclusion

... While the earlier formalisms present a particular set of semantic constraints or axioms as being the formalization of a BDI agent, we adopt the view that one should be able to choose an appropriate BDI system for an application based on the rational behaviours required for that application. As a result, following the modal logic tradition, we have discussed how one can categorize different combinations of interactions between beliefs, desires, and intentions...

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