The Architecture of Expert Systems. The process of building an expert system is often called knowledge engineering It typically involves a special form of interaction between the expert-system builder, called the knowledge engineer, and one or more human experts in some problem area. A rule based expert system consists of the following components: User Interface. The component of an expert system which contains the system’s knowledge in codified form is called its Knowledge base. However, not all rules pertain to the system’s domain, some production rules, called meta-rules, pertain to other production rules (or even to themselves). The component of an expert system which communicates with the user is known as user interface. 12.4. The Expert & the knowledge Engineer should Anticipate Users’ needs & … Human — Machine Interface (Dialogue component). Input/output modes and their effectiveness. An expert system, is an interactive computer-based decision tool that uses both facts and heuristics to solve difficult decision making problems, based on knowledge acquired from an expert. The system defines domain model (including facts about the domain of interest) and domain principles which are heuristics and operators-meta-rules or control rules. For example, the following meta-rule is from MYCIN: (i) If there are rules which do not mention the current goal in their premise. The same difference is exhibited in the table. defined as an interactive and reliable computer-based decision-making system which uses both facts and heuristics to solve complex decision-making problems Suppose a dog has insects in its coat and is scratching its coat. We might of course ask to know why the system needs information about the colour of insects. contained within the system. Expert System Architecture: An ES merges knowledge, facts and reasoning techniques in producing a decision. Architecture of an Expert System . Helps the expert(s) structure the problem area by interpreting and integrating human answers to questions, drawing analogies, posing counter examples, and bringing to light conceptual difficulties. The dialogue could be one of three styles: 1. Rule-Based System Architecture A collection of rules A collection of facts An inference engine We might want to: See what new facts can be derived Ask whether a fact is implied by the knowledge base and already known facts COMP210: Artificial Intelligence. The result is a computer program which solves problem in much the same manner as the human experts (e.s). In addition, it should be able to differentiate between the domain knowledge which it uses and the control knowledge, used to control the search; explanation for users are best described in terms of the domain; those for knowledge engineers in terms of control mechanism. rules and facts to derive conclusions. London: Chapman & Hall Ltd., pp. At this point if we asked for an explanation the following style of response which follows from rule 2 would be given: This traces the reasoning of the type shown above, used through the consultation, so that any errors can be identified and justification can be given to the client, if required. An automatic programmer then uses these to generate the system. As shown in table; the terminology of expert systems can be mapped on a one- to-one basis to that of software programs. If the dog is scratching its coat AND there is hair loss AND there is inflammation THEN the dog should be treated for eczema. Lecture 13. and the user, to infer new facts. System architecture and architecting System architecture is an architecture covering an entity elaborated with a systemic (system-wide) approach. The communication performed by a user interface is bi-directional as shown in the Fig. (The reasoning used here is forward reasoning but backward reasoning, can also be deployed). Knowledge Acquisition. The data in the knowledge base is essentially added by humans who are experts in a particular domain. The fact database contains the case-specific data that are to be THEN the dog should be treated for lice. Briefly, we can say that expert system shells are high level programming languages with unconventional conveniences such as explanation or tracing facilities. user interface which may use menus, natural language or any other style of interaction). Ultimately the expert system achieves high performance by using knowledge to make the best use of its time. One side of the dialogue involves the user questioning the system at any point by using the control strategies and on the other side the system must be able to question the user to establish the existence of evidence. An expert system is typically composed of at least three primary components. Figure shows the most important modules that make up a rule-based expert system. Components of an Expert System 2. Expert System Architecture | Characteristics of Expert System Artificial Intelligence Video Lectures in Hindi The following quote by Paul E. Johnson (1983), a scientist who has spent many year studying the behaviour of human experts quite accurately describes what we mean by the term expert: An expert is a person who, because of training and experience, is able to do things the rest of us cannot; experts are not only proficient but also smooth and efficient in the actions they take. The The knowledge engineer is a person with the qualities of empathy, quick learning, and So the question which papers in this current semester he is to clear does not arise if he has not passed in the 4th semester. During the design of user interface the important points are: 2. User interface. In this architecture, an expert system consultation subsystem provides the means for performing expert consultations. In the user controlled dialogue, the system might not get all the information required. This approach ensures that explanation is considered at the early specification stage, and allows the automatic programmer to use one piece of knowledge in several ways (in problem solving strategy, of explanation providing etc.). examining the data given by the explanation system. The success of any expert system majorly depends on the quality, completeness, and accuracy of the information stored in the knowledge base. The inference engine will use forward Expertise takes a long time (usually several years) to a acquire. examining the data given by the explanation system. engine arrived at its conclusions. At the simplest level we, as user, must be able to describe our problem to the expert system and the system must be able to respond with its recommendations. diagnosis system. The basic idea of intelligent problem-solving is that a system must construct its solution selectively and efficiently from a space of alternatives. The explanation chain shown above is a restatement of the rules used. In the rule-based systems the procedural knowledge; in the form of heuristic ‘if- then’ production rules is completely integrated with the declarative knowledge. This provides a context for the explanation- the user knows not only which rules have been fired but what hypothesis was being considered. user may be able to see this by Terms of Service 7. Integration of Expert systems Components. Knowledge Acquisition Issues and techniques. Expert System Architecture. The knowledge base contains the specific domain Typical expert system architecture is shown in used in a particular case to derive a conclusion. This component of the system is known as control structure, the rule interpreter or inference engine. In addition to questions such as “how did you reach that conclusion?” The user may require explanatory feedback during a consultation, particularly to clarify what information the system requires. This form of explanation facility is far from ideal, both in terms of the way that it provides the explanation and the information to which it has access. An example of such a shell is CLIPS and the above rules constitute knowledge Base (kB). Knowledge engineers building the expert system also need to examine the reasoning behind decisions in order to access and evaluate the mechanisms being used. A knowledge base contains both declarative knowledge (facts about objects, events and situations) and procedural knowledge (information about course of action). information that is contained in the knowledge base. Experts know a great many things and have tricks and caveats for applying what they know to problems and tasks; they are also good at ploughing through irrelevant information in order to get at basic issues, and they are good at recognising problems they face as instances of types with which they are familiar. Architecture of an Expert System. His knowledge spots useful data early, suggests promising ways to exploit them, and helps avoid low-payoff efforts by pruning blind alleys as early as possible. The first expert system was developed in 1965 by Edward Feigenbaum and Joshua Lederberg of Stanford University in California, U.S. The user of the expert system interfaces with it through a user The knowledge base contains the specific domain knowledge that is used by an expert to derive conclusions from facts. Expert System Domains. An Expert system is a domain in which Artificial Intelligencestimulates the behavior and judgement of a human or an organisation containing experts. These components are shown in Fig. An expert system is provided which can be accessed by other application programs operating within any of the available operating environments in a general purpose computer system. We are required to arrive at the theraptic conclusion. Expert system shell contains the special software development environment, and it has basic components of expert system such as – Knowledge-based management system, Workplace, Explanation facility, Reasoning capacity, Inference engine, user interface. Artificial Intelligence/Expert System languages such as LISP, PROLOG, SMALL TALK can be used to build an empty package of the knowledge base, inference engine or user interface. System controlled, where the system drives the dialogue through questioning the user. Moving on with this Expert System In Artificial Intelligence, Main areas of application For example, it is not helpful to ask for the model of the car of a person when the user has already said that, he or she does not possess a car. A typical consultation would begin with a request for information. An expert system has many core system components to function and interfaces with individuals of various roles. (ii) If there are rules which mention the current goal in their premise. This element of the system is so critical to the way the most expert system are constructed that they are also popularly known as knowledge based systems. An expert system is an example of a knowledge-based system. It may be noted that this meta-rule does not contain knowledge related to MYCIN’S domain, but it does contain knowledge which will help the system determine the order in which the rules should be executed. then the user may be able to see this by It enables experts to make better and faster decisions than non-experts in solving complex problems. Expert systems were the first commercial systems to use a knowledge-based architecture. If the dog is scratching its coat AND if insects can be seen in the coat AND if the insects are black THEN the dog should be treated for fleas. This type of user interface is sometimes called a natural language front-end. [gravityform id="1" title="false" description="false" ajax="true"]. It also decides which heuristic search techniques are used in determining how the rules in the knowledge are to be applied to the problem. It is a tool to facilitate the rapid development of an expert system. The explanation can be generated, by creating a goal tree which has been transverse, as explained by the following example of an expert system to diagnose skin diseases in dogs: If the dog is scratching its ears AND the ears are waxy THEN the ears should be cleaned. In order to do this successfully, expert systems must be designed for providing explanation. knowledge that is used by an expert to derive conclusions from facts. The XPLAIN system, links the process of explanation with that of designing the expert system. It is reasonable to suppose, therefore, that experts are the ones to consult when we wish to represent the expertise which makes the behaviour of expert systems possible. If explanation component is not provided it would not be possible to judge whether the expert system is working as desired or intended. Ideally, an explanation facility should be able to direct the explanation towards the skill level or understanding of the user. In an attempt to match the conditions of the first rule “is the dog scratching its ears?”, to which the response of the answer is suppose ‘no’. A knowledge-based system is essentially composed of two sub-systems: the knowledge base and the inference engine. 17-20 3. information are contained within the, CLIPS (C Language Integrated Production System), Backward Chaining in Rule-Based Expert Systems. The two figs, are virtually the same. By simply having access to a great deal of knowledge does not make us an expert, we must know how or when to apply the appropriate knowledge. Before uploading and sharing your knowledge on this site, please read the following pages: 1. Depending on the form of knowledge representation chosen the types of knowledge may be separated or integrated. Even graphics or multi-media interfaces are also used though not very common. The user interface may be a simple text-oriented display or a sophisticated, high resolution display. Artificial intelligence - Artificial intelligence - Expert systems: Expert systems occupy a type of microworld—for example, a model of a ship’s hold and its cargo—that is self-contained and relatively uncomplicated. An expert system is a computer program that uses artificial intelligence technologies to simulate the judgment and behavior of a human or an organization that has expert knowledge and experience in a particular field.. The main components in an Expert System Software are knowledge base, inference engine including explanation facility, user interface mechanism and interfacing, whereas the main components of a conventional software are data (database), program code, interpreter/compiler though not obvious to the user and sparse user-interface. In this case the usual response is to provide a trace up to the rule(s) currently being considered and a restatement of that rule(s). Expert system, a computer program that uses artificial-intelligence methods to solve problems within a specialized domain that ordinarily requires human expertise. from the data that are available to it. system has used faulty reasoning to arrive at its. However, the software is used by non-experts to gain information. For example, Inference engine of MYCIN is available separately as EMYCIN (essential MYCIN). The inference engine uses the information provided to it by the K.B. The knowledge base contains the specific domain knowledge that is used by an expert to derive conclusions from facts. Privacy Policy 9. It acquires relevant knowledge from its knowledge base, and interprets it as per the user’s problem. Note that in Figure 11.1, the parts Although many knowledge represent­ation techniques have been used in expert system the most prevalent form of knowledge representation used in expert system is the rule-based production system approach. Figure 11.1. They can advise users as well as provide explanations to them about how they reached a particular conclusion or advice. In practice a user interface for the system is expected to explain its ‘reasoning’ or the system may request additional information about the problem from us. This technique shows how to communicate with an expert system in ordinary English and enable the computer to respond to us in the same language. Underlying the behaviour of experts in the body of operative knowledge we have termed expertise. system has used faulty reasoning to arrive at its conclusions, The knowledge based approach to expert system design represents: An expert system consists of the following main components: 2. It can be further illustrated with a real-time example in B. Does not clear all papers of the expert system shells are high level languages... 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