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Expert System In Artificial Intelligence is term that is making rounds of the technology world and for all good reasons. In this article we will be exploring this topic in detail.
Following pointers will be covered in this article,
Well, normally the name Artificial Intelligence suggests the Intelligence of a machine which is artificial. The intelligence posses by human is known as human intelligence, like in the same way the intelligence demonstrated by a machine is known as Artificial Intelligence. In computer science. Artificial intelligence(AI), sometimes called machine intelligence. The research field of Artificial Intelligence was born at a workshop at Dartmouth College in 1956.
Applications Of Artificial Intelligence In Real World:
The chatbots like SIRI, CORTANA which have gained so much of popularity in nowadays. Other examples like EVA (Electronic Virtual Assistant), an AI-based chatbot developed by HDFC banks’s AI research department which can collect knowledge from thousands of sources and provide simple answers in less than 0.4 seconds. There are so many examples of AI applications you will find in different field of our society.
What is an expert system?
Researchers of Standford University, Computer Science Department has introduced this domain of AI and it is a prominent research domain of AI. It is a computer application which can solve most complex problems of any specific domain. It is considered at the highest level of human Intelligence and expertise as it is based on knowledge acquired from an expert. Expert System can also be defined as computer-based decision making system that can solve complex decision-making problems using both facts and heuristics.
Expert Systems today
The American Medical Association has approved the first expert system which was Pathfinder system. It was built Standford University in 1980, for hematopathology diagnosis. This decision-theoretic expert system in short Pathfinder, can diagnoses lymph-node diseases. In the end it deals with over 60 diseases and can recognize over 100 symptoms.
Expert system in business
Recently developed an expert system ROSS, the AI attorney, ROSS is a self-learning system that uses data mining, pattern recognition, deep learning and natural language processing to mimic the way the human brain works.
Purpose of Expert System
The main purpose of an expert system is to acquire knowledge of human experts and to replicate that knowledge and skills of human expert in a particular area. Then the system will use that knowledge and skills to solve complex problems of that particular area without human experts participation.
Characteristics of Expert Systems
The main components are:
The process of getting knowledge from experts by interviewing or by observing human experts, reading specific books, etc.
The knowledge base is a container of high quality knowledge. Skills develop through practice and intelligence comes from knowledge without knowledge one cannot proof or one cannot show his or her intelligence, so knowledge is very important to develop skill and to exhibit intelligence. Like, in the same way knowledge is required for machine also to exhibit its intelligence. The accuracy of prediction and also the performance of the system is highly and majorly dependent on the collection of perfect, accurate and precise knowledge.
Now what is knowledge?
Knowledge is data or information. For us human being by reading articles and by reading books or from different resources we used to gather knowledge if we can see the process of gaining and enriching knowledge minutly then we will find that by reading books or by reading articles or from any resources we are fetching and extracting data and information from different sources which we then used to store in our brain. So knowledge is data, knowledge is information. Knowledge is also collection of facts.
Data, information and past experience combined together are termed as knowledge.
Knowledge representation is the method of selecting the most appropriate structures to represent the knowledge. It is the method of organizing and formalizing knowledge in the knowledge base. It is done in the form of IF-THEN-ELSE rules.
Testing the knowledge of ES is correct and complete. This whole process is called knowledge engineering.
In case of knowledge-based ES, the Inference Engine acquires and manipulates the knowledge from the knowledge base to come at a particular solution.
In case of rule based ES,
Inference Engine uses the following strategies −
In Forward Chaining, the Inference Engine gives the outcome by following the chain of conditions and derivations. Whatever the knowledge is feeded in the system it goes through all those knowledges and facts and sorts them before concluding a solution. By forward chaining method, expert system tries to answers, “What can happen next?”
Application of forward chaining: House price prediction, stock prediction, prediction of share market etc.
When something has happened in a particular domain, the Inference Engine tries to find out which condition could have happened in the past for this result. By backward chaining method, expert system tries to answer, “Why this happened?”. By backward chaining method inference engine tries to find out cause or reason.
Advantages of Expert System
Disadvantages of expert system:
This brings us to the end of this article on Expert Systems In Artificial Intelligence.
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