Expert Systems Advantages of Expert System: 1. Can be used by the user more frequently. 2. Can work round the clock. 3. Never “forgets” to ask a question, as a human might. 4. Encourages organizations to clarify the logic of their decision-making. 5. Holds and maintains significant levels of information. 6. Provides consistent answers for repetitive decisions, processes and tasks. Disadvantages of Expert System: 1. Lacks common sense needed in some decision making. 2. Cannot make creative responses as human expert would in unusual circumstances. 3. Domain experts not always able to explain their logic and reasoning. . Errors may occur in the knowledge base, and lead to wrong decisions. 5. Cannot adapt to changing environments, unless knowledge base is changed. Advantages and disadvantages of rule-based expert systems Rule-based expert systems are generally accepted as the best option for building knowledge-based systems. Which features make rule-based expert systems particularly attractive for knowledge engineers? Among these features are: 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.
It also allows a graceful and easy expansion of the expert system. To make the system smarter, a knowledge engineer simply adds some rules to the knowledge base without intervening in the control structure. 50RULE-BASED EXPERT SYSTEMS Dealing with incomplete and uncertain knowledge Most rule-based expert systems are capable of representing and reasoning with incomplete and uncertain knowledge. For example, the rule IF season is autumn AND sky is ‘cloudy’ AND wind is low THEN forecast is clear { cf 0. 1 };forecast is drizzle { cf 1. 0 };forecast is rain { cf 0. }could be used to express the uncertainty of the following statement, ‘If the season is autumn and it looks like drizzle, then it will probably be another wet day today’. The rule represents the uncertainty by numbers called Certainty factors The expert system uses certainty factors to establish the degree of con? dence or level of belief that the rule’s conclusion is true. This topic will be considered in detail in Chapter 3. All these features of the rule-based expert systems make them highly desirable for knowledge representation in real-world problems.
Are rule-based expert systems problem-free? There are three main shortcomings: . Opaque relations between rules . Although the individual production rules tend to be relatively simple and self-documented, their logical interactions within the large set of rules may be opaque. Rule-based systems make it difficult to observe how individual rules serve the overall strategy. This problem is related to the lack of hierarchical knowledge representation in the rule-based expert systems. . Ineffective search strategy The inference engine applies an exhaustive search through all the production rules during each cycle. Expert systems with a large set of rules (over 100 rules) can be slow, and thus large rule-based systems can be unsuitable for real-time applications. . Inability to learn . In general, rule-based expert systems do not have an ability to learn from the experience. Unlike a human expert, who knows when to ‘break the rules’, an expert system cannot automatically modify its knowledge base, or adjust existing rules or add new ones.
The knowledge engineer is still responsible for revising and maintaining the system. Advantages Expert systems use information technology to gain and use human expertise. Obviously, this can be very beneficial to organizations. Expert Systems can: 1. Provide answers for decisions, processes and tasks that are repetitive 2. Hold huge amounts of information 3. Minimize employee training costs 4. Centralize the decision making process 5. Make things more efficient by reducing the time needed to solve problems 6. Combine various human expert intelligences 7.
Reduce the number of human errors 8. Provide strategic and comparative advantages that may create problems for competitors 9. Look over transactions that human experts may not think of Disadvantages However, there are also disadvantages to expert systems, such as: 1. No common sense used in making decisions 2. Lack of creative responses that human experts are capable of 3. Not capable of explaining the logic and reasoning behind a decision 4. It is not easy to automate complex processes 5. There is no flexibility and ability to adapt to changing environments 6.
Not able to recognize when there is no answer Advantages of Expert Systems 1. Permanence – Expert systems do not forget, but human experts may. 2. Reproducibility – Many copies of an expert system can be made, but training new human experts is time-consuming and expensive. 3. If there is a maze of rules (e. g. tax and auditing), then the expert system can “unravel” the maze. 4. Efficiency – can increase through output and decrease personnel costs. Although expert systems are expensive to build and maintain, they are inexpensive to operate.
Development and maintenance costs and e spread over many users. The overall cost can be quite reasonable when compared to expensive and scarce human experts. Cost savings: Wages – (elimination of a room full of clerks) Other costs – (Minimize loan loss) 5. Consistency – With expert systems similar transactions handled in the same way. The system will make comparable recommendations for like situations. Humans are influenced by recency effects (most recent information having a disproportionate impact on judgment) primacy effects (early information dominates the judgment). . Documentation – An expert system can provide permanent documentation of the decision process. 7. Completeness – An expert system can review all the transactions, a human expert can only review a sample. 8. Timeliness – Fraud and/or errors can be prevented. Information is available sooner for decision making 9. Breadth – The knowledge of multiple human experts can be combined to give a system more breadth that a single person is likely to achieve 10. Reduce risk of doing business 11. Consistency of decision making 12.
Entry barriers – Expert systems can help a firm create entry barriers for potential competitors. 13. Differentiation – In some cases, an expert system can differentiate a product or can be related to the focus of the firm. 14. Computer programs are best in those situations where there is a structure that is noted as previously existing or can be elicited Disadvantages of Rule-Based Expert Systems 1. Common sense – In addition to a great deal of technical knowledge, human experts have common sense. It is not yet known how to give expert systems common sense. 2.
Creativity – Human experts can respond creatively to unusual situations, expert systems cannot. 3. Learning – Human experts automatically adapt to changing environments; expert systems must be explicitly updated. Case-based reasoning and neural networks are methods that can incorporate learning. 4. Sensory Experience – Human experts have available to them a wide range of sensory experience; expert systems are currently dependent on symbolic input. 5. Degradation – Expert systems are not good at recognizing when no answer exists or when the problem is outside their area of expertise.
