Expert Systems
Write a Term Paper on types of information systems including but not limited to:
Expert systems (Characteristics, advantages and disadvantages)
Expert systems
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 about knowledge, like an expert, and not by following the procedure of a developer as is the case in conventional programming. The first expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were among the first truly successful forms of AI software.
An expert system has a unique structure, different from traditional programs. It is divided into two parts, one fixed, independent of the expert system: the inference engine, and one variable: the knowledge base. To run an expert system, the engine reasons about the knowledge base like a human. In the 80's a third part appeared: a dialog interface to communicate with users. This ability to conduct a conversation with users was later called "conversational”.
Advantages of expert systems 1. Conversational
Expert systems offer many advantages for users when compared to traditional programs because they operate like a human brain. 2. Quick availability and opportunity to program itself
As the rule base is in everyday language (the engine is untouchable), expert system can be written much faster than a conventional program, by users or experts, bypassing professional developers and avoiding the need to explain the subject.
3. Ability to exploit a considerable amount of knowledge
The expert system uses a rule base, unlike conventional programs, which means that the volume of knowledge to program is not a major concern. Whether the rule base has 10 rules or 10 000, the engine operation is the same. 4. Reliability
The reliability of an expert system is the same as the reliability of a database, i.e. good, higher than that of a
Expert systems (Characteristics, advantages and disadvantages)
Expert systems
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 about knowledge, like an expert, and not by following the procedure of a developer as is the case in conventional programming. The first expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were among the first truly successful forms of AI software.
An expert system has a unique structure, different from traditional programs. It is divided into two parts, one fixed, independent of the expert system: the inference engine, and one variable: the knowledge base. To run an expert system, the engine reasons about the knowledge base like a human. In the 80's a third part appeared: a dialog interface to communicate with users. This ability to conduct a conversation with users was later called "conversational”.
Advantages of expert systems 1. Conversational
Expert systems offer many advantages for users when compared to traditional programs because they operate like a human brain. 2. Quick availability and opportunity to program itself
As the rule base is in everyday language (the engine is untouchable), expert system can be written much faster than a conventional program, by users or experts, bypassing professional developers and avoiding the need to explain the subject.
3. Ability to exploit a considerable amount of knowledge
The expert system uses a rule base, unlike conventional programs, which means that the volume of knowledge to program is not a major concern. Whether the rule base has 10 rules or 10 000, the engine operation is the same. 4. Reliability
The reliability of an expert system is the same as the reliability of a database, i.e. good, higher than that of a