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Abstract - The Visual Development of Rule-Based Systems

     Charles Langley and Clive Spenser present the benefits of representing knowledge with visual rules. Typical text-based rules have the disadvantage that they do not allow the user viewing them to easily grasp the connections between concepts. Using LPA's VisiRule software, the authors demonstrate the creation of a rule-based system from a flow chart. They discuss different types of boxes used in the flow charts using an example of a credit check.


The Visual Development of

Rule-Based Systems


By Charles Langley and Clive Spenser

     In the late 1980's Knowledge Based Systems (KBS) were seen to be leading edge software technology. Developers thought that the simplest KBS paradigm, Expert Systems, perhaps combined with probabilistic and fuzzy logic extensions would soon revolutionise the way that software was used throughout business and other sectors of the economy.
     KBS software was built on rules which encoded the knowledge of experts in any given domain. Computers would then use this encoded knowledge to make decisions on behalf of their human users.
     It was not long however, before the bubble of hype surrounding these systems began to burst. Something was wrong, but what was it?

The Knowledge Acquisition Bottleneck
     Apart from the limited power of the computers available at the time, the major problem was the difficulty of acquiring implicit knowledge from the minds of experts and then representing it explicitly. This so-called Knowledge

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Acquisition Bottleneck was believed to be the limiting factor on building systems that could do complex, useful tasks.
     By the end of the twentieth century however, university departments were working hard at this problem. Curiously it was often Psychology departments rather than Computer Science departments which had the most impact in this area.
     In particular, Ethnography (by then seen as a core part of Cognitive Psychology) was being used to study behaviour in situ with the aim of identifying the cognitive processes underlying that behaviour. Just as Margaret Mead (an early ethnographer) had lived amongst native tribes in Papua New Guinea in order to study their cognitive behaviour, so Psychology departments were sending researchers (often under cover) into workplace environments to discover how people approached problem-solving activities.
     This work was, and continues to be, very successful. Knowledge acquisition is no longer the 'black art' it was deemed to be. Despite this, KBS has continued to be underused. Why might this be?

A Knowledge Representation Bottleneck?
     It is my contention that the problem was not primarily with how we obtained knowledge, but with how we represented it. I am not arguing that rules (or Bayesian networks and other knowledge representation methods) are inadequate to the

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