Expert systems are computer-based interactive systems that are capable of making decisions that are similar to those made by practicing professionals or experts in a particular field. Expert systems are also called knowledge-based systems because they are designed to capture and represent the knowledge of an expert in a particular field.
Expert systems are used to provide advice, recommendations or solutions in a variety of fields like medical diagnosis, financial analysis, legal advice, and product design. These systems can be designed to be standalone applications or run as a part of a larger software system.
Expert systems are built by capturing the knowledge of an expert in a particular field and representing it as a set of rules, cases, or algorithms. The knowledge is then encoded into the knowledge base of the system. The knowledge base is the central component of the expert system and contains the knowledge that the system uses to make decisions or provide advice.
The knowledge base is not a static component of the system. It can be constantly updated with new data, cases and rules to ensure that the knowledge base of the system is always up-to-date.
Expert systems can be classified into two types: knowledge-based expert systems and rule-based expert systems. In knowledge-based systems, the knowledge is represented in a graphical format that is easily understandable by the user. In rule-based systems, the knowledge is represented as a set of rules that are applied to a set of input data to generate an output.
Expert systems have several advantages over traditional decision-making systems. They are capable of handling large amounts of information and can provide consistent and reliable advice. Expert systems can also be used to train new employees or educate students in a particular field.
One of the major limitations of expert systems is that they require a significant amount of time and resources to develop. Expert systems must be developed by experts in a particular field who can provide accurate and reliable knowledge. This means that the development of an expert system can take several months or even years.
Another limitation of expert systems is that they are only capable of providing advice or recommendations based on the knowledge that has been encoded into their knowledge base. They are not capable of learning from new experiences or adapting to new situations.
Despite these limitations, expert systems are being used in a wide range of applications, from medical diagnosis to legal advice. With advancements in artificial intelligence and machine learning, expert systems are becoming more sophisticated and capable of handling complex problems.
In conclusion, expert systems are computer-based interactive systems that are capable of making decisions similar to those made by experts in a particular field.