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Popular posts from this blog

Artificial Intelligence --Terminology

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Artificial Intelligence --Terminology Here is the list of frequently used terms in the domain of AI − Sr. No Term & Meaning 1 Agent Agents are systems or software programs capable of autonomous, purposeful and reasoning directed towards one or more goals. They are also called assistants, brokers, bots, droids, intelligent agents, and software agents. 2 Autonomous Robot Robot free from external control or influence and able to control itself independently. 3 Backward Chaining Strategy of working backward for Reason/Cause of a problem. 4 Blackboard It is the memory inside computer, which is used for communication between the cooperating expert systems. 5 Environment It is the part of real or computational world inhabited by the agent. 6 Forward Chaining Strategy of working forward for conclusion/solution of a problem. 7 Heuristics It is the knowledge based on Trial-and-error, evaluations, and experimentation. 8 Knowledge Engin
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Artificial Intelligence -- Fuzzy logic

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Artificial Intelligence -- Fuzzy logic Fuzzy Logic Systems (FLS) produce acceptable but definite output in response to incomplete, ambiguous, distorted, or inaccurate (fuzzy) input. What is Fuzzy Logic? Fuzzy Logic (FL) is a method of reasoning that resembles human reasoning. The approach of FL imitates the way of decision making in humans that involves all intermediate possibilities between digital values YES and NO. The conventional logic block that a computer can understand takes precise input and produces a definite output as TRUE or FALSE, which is equivalent to human’s YES or NO. The inventor of fuzzy logic, Lotfi Zadeh, observed that unlike computers, the human decision making includes a range of possibilities between YES and NO, such as − CERTAINLY YES POSSIBLY YES CANNOT SAY POSSIBLY NOCERTAINLY NO The fuzzy logic works on the levels of possibilities of input to achieve the definite output. IMPLEMENTATION It can
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Artificial Intelligence -- Expert system

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Artificial Intelligence -- Expert system Expert systems (ES) are one of the prominent research domains of AI. It is introduced by the researchers at Stanford University, Computer Science Department. What are Expert Systems? The expert systems are the computer applications developed to solve complex problems in a particular domain, at the level of extra-ordinary human intelligence and expertise. CHARACTERISTICS OF EXPERT SYSTEMS High performance Understandable Reliable Highly responsive Capabilities of Expert Systems The expert systems are capable of − Advising Instructing and assisting human in decision making Demonstrating Deriving a solution Diagnosing Explaining Interpreting input Predicting results Justifying the conclusion Suggesting alternative options to a problem They are incapable of − Substituting human decision makers
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