Expert system is a computer program that uses artificial intelligence technologies to solve complex problems in a particular field and enhance the decision-making capability of a human expert. The computer program contain expert knowledge base to respond correctly. ES gives high performance and are reliable enough.
ES are designed to solve complex problems by reasoning through knowledge bodies. Knowledge is represented mainly as if–then rules rather than conventional procedural code.
Expert system was introduced by Edward Feigenbaum during the Stanford Heuristic Programming Project. Edward Feigenbaum is also known as the father of expert systems. The first expert system that was used in a design capacity for a large-scale product was the SID (Synthesis of Integral Design) software program. It was developed in 1982. It was written in LISP programming.
What is Expert System?
ES are intelligent computer applications that uses control mechanism, data and knowledge base to resolve complex problems that cannot be done without an experienced and expertise human being. It applies Problem Solving skills and knowledge representation techniques of Artificial Intelligence to combine human expert knowledge about a problem with human expert methods of conceptualizing and reasoning about that problem. As the name represents an expert system is an expert the particular field it is serving, we can expect such systems to perform better in comparison of a human expert in that specialized problem area. Expert systems do not pretend to give final or ultimate conclusions to displace human decision making; they are used for consulting purposes only.
Components of Expert System
We can divide an expert system into three subsystems: the inference engine, the knowledge base and the user interface. The knowledge base represents facts and rules. The inference engine applies the rules to the known facts to deduce new facts. Inference engines can also include explanation and debugging abilities. User Interface provides communication access between user and the system. Let us discuss about the components one by one.
Knowledge base contains expert level knowledge of a particular field that is stored in knowledge representational form. Knowledge is required to exhibit intelligence. The success of any ES majorly depends upon the collection of highly accurate and precise knowledge.
Data, information, and past experience combined together are known as Knowledge. The knowledge base of an ES is stores both factual and heuristic knowledge. Factual Knowledge is the information widely accepted by the Knowledge Engineers and scholars in the task domain while Heuristic Knowledge is about practice, accurate judgement, one’s ability of evaluation, and guessing.
Inference engine is a software used to perform the task of inference reasoning. It uses the knowledge which is stored in the knowledge base and then the information is provided by the user to conclude a new knowledge. It is essential to use efficient procedures and rules by the Inference Engine to deduct a correct, flawless solution.
It applies rules repeatedly to the facts obtained from earlier rule application, adds new knowledge to the knowledge base if required, and resolves rules conflict if multiple rules are applicable to a particular case.
Inference engine also uses Forward chaining and Backward chaining strategies for conclusion. In Forward Chaining, Inference Engine follows the chain of conditions and derivations and finally obtain the outcome. It considers all the facts and rules, and sort them before telling the conclusion of a solution. This strategy is applicable for working on conclusion, result, or effect. In Backward Chaining, the Inference Engine tries to find out which conditions could have happened in the past for this result. This strategy is applicable for finding out the reason.
User interface allows user to interact with the expert system. It generally uses Natural Language Processing so that the user can easily work in a friendly environment. It is not mandatory that the user of an ES will be an expert in Artificial Intelligence. It explains how the ES has arrived at a particular recommendation.
A shell is a specially designed tool on the basis of the requirements of particular application so that the user provides the knowledge base to the shell. A shell provides the developers with knowledge acquisition, inference engine, user interface, and explanation facility.
Advantages of Expert Systems
- Knowledge Sharing.
- Reduces errors and inconsistency
- Allows non expert users to reach scientifically proven conclusions.
- Affordable and Reliable.
- Reduces risks and gives steady performance.
Limitations of Expert System
Though ES are advanced enough and performs well, it has some limitations as well.
- Limitations of the technology
- High development costs
- Difficult knowledge acquisition
- ES are difficult to maintain
Applications of Expert System
The application of ES has spread mostly in the fields of knowledge works.
Diagnosis and troubleshooting of devices: deduce faults and suggest corrective actions for a malfunctioning device or process. Medical diagnosis was one of the first knowledge areas to which ES technology was applied but diagnosis of engineered systems quickly surpassed medical diagnosis.
Planning and scheduling: analyze a set of one or more potentially complex and interacting goals in order to determine a set of actions to achieve those goals, and/or provide a detailed temporal ordering of those actions, taking into account personnel, materiel, and other constraints. Example: airline scheduling of flights, personnel, and gates; manufacturing job-shop scheduling.
Configuration of manufactured objects from sub assemblies: Configuration applications were pioneered by computer companies as a means of facilitating the manufacture of semi-custom minicomputers. Example: modular home building, manufacturing, and other problems involving complex engineering design and manufacturing.
Financial decision making: Advisory programs have been created to assist bankers in determining whether to make loans to businesses and individuals. Insurance companies have used expert systems to assess the risk presented by the customer and to determine a price for the insurance. A typical application in the financial markets is in foreign exchange trading.
Knowledge Publishing: to deliver knowledge that is relevant to the user’s problem, in the context of the user’s problem. The two most widely distributed expert systems in the world are in this category. The first is an adviser which counsels a user on appropriate grammatical usage in a text. The second is a tax adviser that accompanies a tax preparation program and advises the user on tax strategy, tactics, and individual tax policy.
Process monitoring and control: analyze real-time data from physical devices with the goal of noticing anomalies, predicting trends, and controlling for both optimal and failure correction. Example: steel making and oil refining industries.
Design and manufacturing: assist in the design of physical devices and processes, ranging from high-level conceptual design of abstract entities all the way to factory floor configuration of manufacturing processes.
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