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The construction of large-scale embedded software systems demands the use of design methodologies and modelling techniques that support abstraction, inheritance, modularity, and other mechanisms for reducing complexity and preventing error. If multi-agent systems are to become widely accepted as a basis for large-scale applications, adequate agent-oriented methodologies and modelling techniques will be essential. This is not just to ensure that systems are reliable, maintainable, and conformant, but to allow their design, implementation, and maintenance to be carried out by software analysts and engineers rather than researchers. In this paper we describe an agent-oriented methodology and modelling technique for systems of agents based upon the Belief-Desire-Intention (BDI) paradigm. Our models extend existing Object-Oriented (OO) models. By building upon and adapting existing, well-understood techniques, we take advantage of their maturity to produce an approach that can be easily learnt and understood by those familiar with the OO paradigm.

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The development of systems capable of handling and diagnosing malfunctions in real time has long been of considerable practical importance. This paper describes the architecture of such a system, called the Procedural Reasoning System (PRS). PRS is based on the notion of a rational agent that can reason and plan under possibly stringent constraints on both time and information. This approach p r o vides the system with the ability to reason in complex ways about dynamic processes, while still maintaining the reactivity required to ensure appropriate responsiveness and control. By considering two large-scale applications in aerospace and telecommunications, it is shown how PRS meets many of the critical requirements for real-time malfunction-handling and diagnostic systems. Finally, PRS is compared with a number of other real-time reasoning and knowledge-based architectures that have been used in similar applications.

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