Expert Systems
In artificial intelligence, expert systems are computer systems that simulate the decision-making capabilities of human experts.Expert system is the most important and active application field in artificial intelligence. It has achieved a major breakthrough in the transition of artificial intelligence from theoretical research to practical application, and from the discussion of general reasoning strategies to the use of specialized knowledge. Expert system is an important branch of early artificial intelligence. It can be regarded as a type of computer intelligent program system with specialized knowledge and experience. It generally uses knowledge representation and knowledge reasoning technology in artificial intelligence to simulate complex problems that can usually only be solved by experts in the field. Expert system is widely used in medical diagnosis, accounting, coding, games and other fields.
Components of an expert system
- knowledge base: The knowledge base represents facts and rules. It consists of knowledge in a specific domain as well as rules, processes for solving problems, and intrinsic data related to the domain.
- Inference Engine: The function of an inference engine is to obtain relevant knowledge from a knowledge base, interpret it, and find solutions relevant to the user's problem. An inference engine obtains rules from its knowledge base and applies them to known facts to infer new facts. An inference engine can also include explanation and debugging capabilities.
- Knowledge acquisition and learning modules: The function of this component is to allow the expert system to acquire more and more knowledge from various sources and store it in the knowledge base.
- user interface : This module enables non-expert users to interact with the expert system and find solutions to problems.
- Explanation module: This module helps the expert system explain to the user how the expert system reached a specific conclusion.