Lecture10
The explanation
· A unique feature of an expert system is its explanation capability. It enables the expert system to review its own reasoning and explain its decisions.
· The explanation facilities enable the user to ask the expert system how a particular conclusion is reached and why a specific fact is needed. An expert system must be able to explain its reasoning and justify its advice, analysis or conclusion.
l Types of Explanation
l There are four types of explanations commonly used in expert systems.
l ‡ Rule trace reports on the progress of a consultation;
l ‡ Explanation of how the system reached to the given conclusion;
l ‡ Explanation of why the system did not give any conclusion.
l ‡ Explanation of why the system is asking a question;
User Interface
The user interface is the means of communication between a user seeking a solution to the problem and an expert system.
? User Interface A means of communication with the user. The user interface is generally not a part of the expert system technology. It was not given much attention in the past. However, the user interface can make a critical difference in the perceived utility of an Expert system.
Can expert systems make mistakes?
· Even a brilliant expert is only a human and thus can make mistakes. This suggests that an expert system built to perform at a human expert level also should be allowed to make mistakes. But we still trust experts, even we recognise that their judgements are sometimes wrong. Likewise, at least in most cases, we can rely on solutions provided by expert systems, but mistakes are possible and we should be aware of this.
How do we choose between forward and backward chaining?
· If an expert first needs to gather some information and then tries to infer from it whatever can be inferred, choose the forward chaining inference engine.
· However, if your expert begins with a hypothetical solution and then attempts to find facts to prove it, choose the backward chaining inference engine.
Advantages of rule-based expert systems
· Natural knowledge representation. An expert usually explains the problem-solving procedure with such expressions as this: “In such-and-such situation, I do so-and-so”. These expressions can be represented quite naturally as IF-THEN production rules.
· Uniform structure. Production rules have the uniform IF-THEN structure. Each rule is an independent piece of knowledge. The very syntax of production rules enables them to be self-documented.
· Separation of knowledge from its processing. The structure of a rule-based expert system provides an effective separation of the knowledge base from the inference engine. This makes it possible to develop different applications using the same expert system shell.
· Dealing with incomplete and uncertain knowledge. Most rule-based expert systems are capable of representing and reasoning with incomplete and uncertain knowledge.
المادة المعروضة اعلاه هي مدخل الى المحاضرة المرفوعة بواسطة استاذ(ة) المادة . وقد تبدو لك غير متكاملة . حيث يضع استاذ المادة في بعض الاحيان فقط الجزء الاول من المحاضرة من اجل الاطلاع على ما ستقوم بتحميله لاحقا . في نظام التعليم الالكتروني نوفر هذه الخدمة لكي نبقيك على اطلاع حول محتوى الملف الذي ستقوم بتحميله .