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Title: Connectionism in expert systems
Author: MacRae, John R.
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 1989
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As the technology of computer systems matures, it is becoming clear that conventional techniques are inadequate for complex applications, and attention is being increasingly directed at the use of Knowledge-Based Systems technology. Critical problems in Knowledge-Based Systems are the representation of the expertise from the selected application, and in harnessing sufficient computing power to utilise the stored expertise. An idea which is currently popular in Artificial Intelligence research is that of using parallel processing to ensure that the expertise or knowledge is used effectively, within realistic timescales. Proposals vary in the degree of parallelism, and in the distribution of the problem solving activities. The theory of connectionism, which proposes that the knowledge representation and the problem solving computations are distributed across a very large number of processors, has generated considerable interest and response. Connectionist machines, sometimes known as massively parallel processors, are not highly parallel versions of conventional problem solving engines, but combine the representation of the problem with the processing to produce what is known as an active memory network. Research is described which investigates the application of connectionist theory to various complex problems. These problems are investigated within the context of conventional knowledge-based systems, with the aim of establishing if massively parallel technology realises an efficient problem solving engine. The difficulties associated with the representation and use of numbers in connectionist networks are addressed, the problem of relating the knowledge representation in expert systems to that in connectionist networks is resolved, and the potential for medium scale parallelism in knowledge-based systems is contrasted with the parallelism of connectionism. Finally, the vision of an ideal problem solving engine is considered; some aspects of the evolving designs approach this ideal, and are described.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Computer software & programming Computer software Electric engineering Computer science