EXPERT SYSTEMS
What is an Expert System in AI ?
Expert systems (ES) are one of the prominent research domains of AI. It is introduced by the researchers at Stanford University, Computer Science Department.
In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if-then rules rather than through conventional procedural code.
Expert systems have specific knowledge to one problem domain, e.g., medicine, science, engineering, etc. The expert’s knowledge is called a knowledge base, and it contains accumulated experience that has been loaded and tested in the system. Much like other artificial intelligence systems, expert system’s knowledge may be enhanced with add-ons to the knowledge base, or additions to the rules. The more experience entered into the expert system, the more the system can improve its performance.
Architecture :
Characteristics of expert systems:
- Highly responsive
- Reliable
- Understandable
- High performance
Capabilities and Incapablilities of Expert Systems :
- Advising
- Instructing and assisting human in decision making
- Demonstrating
- Deriving a solution
- Diagnosing
- Explaining
- Interpreting input
- Predicting results
- Justifying the conclusion
- Suggesting alternative options to a problem
- Substituting human decision makers
- Possessing human capabilities
- Producing accurate output for inadequate knowledge base
- Refining their own knowledge
Maintain the System :
- Keep the knowledge base up-to-date by regular review and update.
- Cater for new interfaces with other information systems, as those systems evolve.
Benefits of Expert Systems :
- Availability − They are easily available due to mass production of software.
- Less Production Cost − Production cost is reasonable. This makes them affordable.
- Speed − They offer great speed. They reduce the amount of work an individual puts in.
- Less Error Rate − Error rate is low as compared to human errors.
- Reducing Risk − They can work in the environment dangerous to humans.
- Steady response − They work steadily without getting motional, tensed or fatigued.
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