Expert System
An Expert System is a reasoning system that is an expert in some expertise domain.
- Context:
- It can be produced by an Expert System Engineering Task.
- It can (typically) make use of a Formal Knowledge Base.
- It can be a Deductive Reasoning System (whose rule-based model captures expert knowledge).
- It can be the area of study for an Expert Systems Field.
- It can be a type of Artificial Intelligence (AI) that emulates the decision-making abilities of a human expert.
- …
- Example(s):
- a Medical Diagnosis System such as:
- a Stock Market Prediction System such as:
- a Legal Expert System such as:
- …
- Counter-Example(s):
- See: DENDRAL System, Deductive Reasoning, Expert System Shell, Modus Tollens, Forward Chaining, Production Computing System, Inference Computing System, Artificial Intelligence, Machine Learning,
References
2023a
- (ChatGPT, 2023) ⇒ "What is an "Expert System"? Explain in 2-3 paragraphs." prompt. ChatGPT, September 25 Version, OpenAI, 29 Oct. 2023. https://chat.openai.com.
- An expert system is a type of artificial intelligence (AI) program that simulates the decision-making ability of a human expert in a specific domain or field. It is designed to solve complex problems or provide expert-level advice by utilizing a knowledge base and a set of inference rules. Expert systems are particularly valuable when there is a need to make decisions or solve problems based on a large amount of specialized knowledge.
The core components of an expert system include a knowledge base, which stores factual information and expertise relevant to the specific domain, and an inference engine, which applies logical reasoning and rules to make deductions and generate solutions. Users interact with the expert system through a user interface, posing questions or presenting problems, and the system uses its knowledge base and inference engine to provide expert-like responses and recommendations. Expert systems have been applied in a wide range of fields, including medicine, engineering, finance, and troubleshooting, to streamline decision-making processes, improve problem-solving capabilities, and assist human experts in their work.
Overall, expert systems are valuable tools that leverage AI techniques to capture and apply specialized knowledge, making them an effective means of transferring and preserving expertise and aiding in decision-making processes within various domains.
- An expert system is a type of artificial intelligence (AI) program that simulates the decision-making ability of a human expert in a specific domain or field. It is designed to solve complex problems or provide expert-level advice by utilizing a knowledge base and a set of inference rules. Expert systems are particularly valuable when there is a need to make decisions or solve problems based on a large amount of specialized knowledge.
2023b
- (Wikipedia, 2023) ⇒ https://en.wikipedia.org/wiki/Expert_system Retrieved:2023-10-29.
- In artificial intelligence, an expert system is a computer system emulating the decision-making ability of a human expert.[1]
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. The first expert systems were created in the 1970s and then proliferated in the 1980s.[2] Expert systems were among the first truly successful forms of artificial intelligence (AI) software.[3] An expert system is divided into two subsystems: the inference engine and the knowledge base. 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.
- In artificial intelligence, an expert system is a computer system emulating the decision-making ability of a human expert.[1]
- ↑ Jackson, Peter (1998). Introduction To Expert Systems (3 ed.). Addison Wesley. p. 2. ISBN 978-0-201-87686-4.
- ↑ Leondes, Cornelius T. (2002). Expert systems: the technology of knowledge management and decision making for the 21st century. pp. 1–22. ISBN 978-0-12-443880-4.
- ↑ Russell, Stuart; Norvig, Peter (1995). "Artificial Intelligence: A Modern Approach" (PDF). Simon & Schuster. pp. 22–23. ISBN 978-0-13-103805-9. Archived from the original (PDF) on 5 May 2014. Retrieved 14 June 2014.