Can Expert Systems Make Mistakes?

Which of the following is incorrect expert system limitation?

Which of the following is incorrect Expert Systems Limitations.

Explanation: Easy to maintain is incorrect Expert Systems Limitations..

Which of the following is an example of expert system?

Examples of Expert Systems Following are the Expert System Examples: MYCIN: It was based on backward chaining and could identify various bacteria that could cause acute infections. … It is one of the best Expert System Example. DENDRAL: Expert system used for chemical analysis to predict molecular structure.

What is the main issue in expert system development?

These issues include: task selection; the stages of development of expert system projects; knowledge acquisition; languages and tools; development and run-time environments; and organizational and institutional issues.

What is rule based expert system in AI?

A rule-based expert system is the simplest form of artificial intelligence and uses prescribed knowledge-based rules to solve a problem 1. … The aim of the expert system is to take knowledge from a human expert and convert this into a number of hardcoded rules to apply to the input data.

Can an expert system make mistakes Why?

Insofar as they are developed to mimic or replace the reasoning and decision-making of human experts, expert computer systems are doomed to make mistakes. The problem of expert systems fallibility and its potential consequences are discussed. Categories of expert systems fallibility are presented and evaluated.

What are the disadvantages of expert system?

However, there are also disadvantages to expert systems, such as:No common sense used in making decisions.Lack of creative responses that human experts are capable of.Not capable of explaining the logic and reasoning behind a decision.It is not easy to automate complex processes.More items…

What is the main purpose of expert systems?

Question 1 What is the main purpose of Expert Systems? Answer: The main purpose of ES is to replicate knowledge and skills of human experts in a particular area, and then to use this knowledge to solve similar problems without human experts participation (computationally).

What are the main components of an expert system?

An expert system generally consists of four components: a knowledge base, the search or inference system, a knowledge acquisition system, and the user interface or communication system. Knowledge systems solve difficult problems of the real woorld by performing inference processes on explicitly stated knowledge.

What are the types of expert system?

There are mainly five types of expert systems. They are rule based expert system, frame based expert system, fuzzy expert system, neural expert system and neuro-fuzzy expert system. We discussed the expert systems based on their knowledge representation, inference engine, working of the system and user interface.

What are the problems faced in expert systems?

Not surprisingly, expert systems have run into a significant problem: they are brittle. When faced with a problem which bends the rules, they are unable to cope. They fail because they are not grounded in cases. They are unable to fall back on the details of their experience, find a similar case, and apply it.

Which of the following is an incorrect application of the expert system?

Explanation: The components of ES include : Knowledge Base, Inference Engine, User Interface. 4. Which of the following is incorrect application of Expert System? … Explanation: Time is not Benefits of Expert Systems.

What do you call someone who is an expert in their field?

Some common synonyms of expert are adept, proficient, skilled, and skillful. While all these words mean “having great knowledge and experience in a trade or profession,” expert implies extraordinary proficiency and often connotes knowledge as well as technical skill.