It is advocated that the same perspective and vocabulary be used during analysis, design, and construction of software systems guided by reference architectures. This method of software construction helps reduce cognitive dissonance through the use of constructs in software that can be mapped more naturally and directly to real-world entities than basic objects. In addition, agents can be integrated frameworks that contain, in one package, specific problem-solving functions, data and control. Going beyond today's business objects, intelligent business agents are the next higher level of abstraction in model-based solutions to business problems. By building on the distributed object foundation, intelligent agent technology can help bridge the remaining gap between flexible design and useable applications.
Intelligent agents support a natural merging of object orientation and knowledge-based technologies.
In many cases, the need for communication is greatly reduced, as within these high-level dialogues, complex packets of procedural and declarative knowledge as well as state information may be exchanged in the form of mobile agents. Figure 3 shows an example of an intelligent agent specializing in supporting risk management. It shows that such an agent would use its knowledge of risk assessment, its role in supporting this process and historical data to examine various data feeds in order to compose a risk exposure picture. Risk Management Application of Intelligent Agents . . Figure 4 illustrates a community of intelligent agents, including a Risk Assessment Agent, supporting a financial trader.