Conclusions

The main conclusions of this thesis work are now presented on a chapter by chapter basis.

In Chapter 3, a comprehensive analysis of the arguments for hybrid systems is carried out using the results of the survey performed on expert systems and neural networks, in Chapter 2. This analysis leads to the formulation of the hybrid classification scheme. This examination continues with the investigation of methods of integrating expert systems and neural networks. These investigations gave some insight into the problems that future hybrid systems may encounter. The conclusions that can be drawn from this analysis are:

Both symbolic and adaptive processing have a narrow area of competence and outside this area they function poorly

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• Symbolic and adaptive systems have complementary strengths and weaknesses especially in the areas of knowledge acquisition, brittleness, high-level and low- level reasoning, and explanation. By integrating these two fundamentally different models of computation one can avoid many of the weaknesses inherent in each methodology, whilst capitalising on their individual strengths.

• Most real-world problems are too complex for any single processing technique to solve in isolation. Most real-world domains have both “logical”, static components (that can be easily handled by symbolic techniques) and fuzzy, dynamic, poorly understood components (which can be handled by adaptive processing techniques). • Hybrid systems can be classified with respect to factors such as functionality,

processing architecture and communication requirements to form three classes : Function-replacing, Intercommunicating and Polymorphic hybrid systems.

• There are many ways that neural networks and experts systems can be combined to utilise their strengths within a hybrid solution.

• Problems may occur in the future with hybrid systems in relation to efficient communication, learning and explanation. Although these problems may exist, they can be reduced by following the proposed development cycle for hybrid systems. In Chapter 4, an object-oriented methodology is advocated as the most pragmatic method of constructing hybrid systems. Various properties and advantages of object- oriented integration for building hybrid systems are discussed. It can be concluded that :

• Intercommunicating hybrids require Design, Communication and Execution Autonomy.

• With an object-oriented approach, techniques can be integrated with communication being conducted through a well-defined message interface and they can be autonomous because components may independently and transparently change internally provided their interfaces are maintained.

• Object-oriented message passing is a well defined communications protocol that allows links to be established at runtime.

• Employing object-oriented techniques allows the ability to manage concurrency because message passing systems are adaptable to many types of hardware environments, including parallel multi-processor and distributed machines.

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• Code can be reused, this allows for multiple copies of the same processing technique. Therefore, chained processing can occur where a combination of techniques can pass data between themselves.

In Chapter 5, the implementation details of the ORBERON object-oriented hybrid environment are discussed in depth. The design and implementation of the fundamental elements of the environment are explained. The neural network and expert systems objects are also described with relation to how they are integrated into the O r b e r o n environment. It can be concluded that :

• that object-oriented methodology is ideally suited for constructing hybrid systems especially intercommunicating hybrid systems. The utilisation of object-oriented benefits such as inheritance, polymorphism and code reuse are fundamental in the design, construction and functioning of the core elements of the environment. In Chapter 6, two real-world problems that were solved using the O r b e r o n

environment are analysed in detail. The first was a proof of concept application for profit trend analysis, that could advise portfolio managers whether to increase, maintain or decrease investment in a particular company. The second application was a complex real- world application from British Airways for the consignment of cargo. This basically involved the processing of cargo consignments for a particular flight and making a decision whether to accept or reject the cargo consignment. The goals being to optimise space and profit. The conclusions reached from the solution of these problems are :

that real-world problems are too complex for either symbolic or adaptive techniques to solve in isolation, but require the strengths of both symbolic and adaptive processing.

that a hybrid approach produced better results for British Airways, than a solution constructed from a single processing technique, namely an expert system.

• the O r b e r o n environment performed efficiently and allowed the design, communication and execution autonomy required by hybrid applications.

• the use of object-oriented programming allowed the flexibility and extendibility required by the O r b e r o n environment.

In Chapter 7, the design and implementation details of the Esprit III HANSA project are described. This project was inspired by the work presented in this thesis and it can be conclude that:

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• the theories and functional concepts presented in this thesis are applicable to the production of a large scale commercial environment for producing hybrid applications.

• the object-oriented com ponents found in the O r b e r o n environment are simphstic in comparison to emerging object-oriented integration m ethods (such as OLE and

CORBA), but their functionality m atches com ponents within these elaborate integration methods.

In Chapter 8, an assessment is carried of the hybrid classification scheme, the

O r b e r o n environment and the British Airways cargo consignment problem. The results from the cargo consignment hybrid solution are compared with the results of the purely symbolic British Airways ASP (Acceptable Shipment Package) system. The conclusions that were reached from this analysis are :

• the hybrid classification scheme provides a clear definition of hybrid systems.

• the hybrid classification scheme provides a means of comparing different hybrid systems.

• due to the complex nature of the Cargo Consignment problem, there were sections of the problem that required the use of neural networks to perform pattern classification and expert systems to co-ordinate the neural networks and make high-level logical decisions based on the results of the neural networks.

• that the hybrid solutions can improve the quality and accuracy of the decisions in comparison to the decisions from the current symbolic Acceptable Shipment Package used by British Airways.

• that the hybrid solution can help to improve the quality, reliability and time taken to make the final decisions by the human Cargo Consignment officer.

• the basic design concepts and principles that characterise the functionality of the core elements of the environment, have functional similarities to components found in current commercial object-oriented integration methods such as the OMG’s Object Request Broker, and Microsoft’s Object Linking and Embedding.