Graded BDI Models for Agent Architectures

In the recent past, an increasing number of multiagent systems (MAS) have been designed and implemented to engineer complex distributed systems. Several previous works have proposed theories and architectures to give these systems a formal support. Among them, one of the most widely used is the BDI agent architecture presented by Rao and Georgeff. We consider that in order to apply agents in real domains, it is important for the formal models to incorporate a model to represent and reason under uncertainty. With that aim we introduce in this paper a general model for graded BDI agents, and an architecture, based on multi-context systems, able to model these graded mental attitudes. This architecture serves as a blueprint to design different kinds of particular agents. We illustrate the design process by formalising a simple travel assistant agent.

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