AI handles more comprehensive problems of automating a system. To solve complex problems; Expert systems are the computer applications; developed in a particular domain, at the level of unusual human intelligence and expertise. Expert systems (ES) are one of the main areas of AI research. It is introduced by researchers from Stanford University, Department of Computer Science. This computerization should be possible using any field such as image processing, cognitive science, neural systems, machine learning, etc. AI plays an important role in managing the manufacturing of savvy machines, frames and different gadgets by allowing them to think and run errands like everyone else usually does.
Expert Systems in Artificial Intelligence (AI):
An expert system is a field in which artificial intelligence stimulates the behavior and judgment of a human or an organization containing experts. It acquires relevant knowledge from its knowledge base and interprets it according to the user’s problem. Knowledge base data is basically added by humans who are experts in a particular field. However, the software is used by non-experts to obtain information. It is used in various fields of medical diagnosis, accounting, coding, games and more.
Importance of the expert system in artificial intelligence:
Improves the quality of decision making. Cost effective, as it reduces the cost of consulting human experts when solving a problem. Provides fast and robust solutions to complex problems in a specific area. It gathers rare knowledge and uses it effectively. When talking about the features of expert systems, high performance levels are the first and foremost thing. These systems are easy to understand, totally reliable and very responsive. In addition, expert systems are capable of a number of actions, including:
• Help in human decision making
• Demonstrations and guidelines
• Originating solutions
• Understanding inputs and providing pertinent outputs
• Forecasting results
• Explanation of conclusions
• Recommendations for alternative solutions to a problem
Expert Systems Limitations:
No technology can offer a simple and complete solution. Large systems are expensive, require significant development time and IT resources. ES have their limitations which include –
• Restrictions of the technology
• Difficult knowledge gaining
• ES are hard to maintain
• High development expenses
Applications of Expert System:
The following details shows where ES can be applied.
1. Design Dominion
Camera lens design and automobile design.
2. Medical Dominion
Diagnosis Systems to infer cause of disease from experiential data, conduction medical processes on humans.
3. Monitoring Methods
Comparing data constantly with observed system or with recommended behavior such as leakage checking in lengthy petroleum pipeline.
4. Process Regulator Systems
Controlling a physical procedure based on monitoring.
5. Knowledge Domain
Searching out faults in vehicles, computers.
An expert system is any computerized decision-making system that is interactive and reliable in solving complex problems. An expert system is used for applications such as human resources, stock market, etc. The main advantages of expert systems are better decision quality, cost reduction, consistency, speed and reliability. An expert system does not provide ready-to-use solutions and the maintenance cost is high.