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27 Cards in this Set
- Front
- Back
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the ability of computers to mimic or duplicate the functions of the human brain
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Artificial Intelligence
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people, procedures, hardware, software, data, and knowledge needed to develop computer systems and machines that demonstrate the characteristics of intelligence
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Artificial Intelligence System
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the ability to learn from experiences and apply knowledge acquired from experience, handle complex situations, solve problems when important information is missing, determine what is important, react quickly and correctly to a new situation, understand visual images, process and manipulate symbols, be creative and imaginative, and use heuristics
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Intelligent Behaviour
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a system that approximates the way a human sees, hears, and feels objects
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Perceptive system
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hardware and software that store knowledge and make inferences, similar to a human expert
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Expert system
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mechanical or computer devices that perform tasks requiring a high degree of precision or that are tedious or hazardous for humans
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Robotics-
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the hardware and software that permit computers to capture, store and manipulate visual images and pictures
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Vision system-
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processing that allows the computer to understand and react to statements and commands made in a “natural” language, such as English
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Natural language processing-
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a combination of software and hardware that allows the computer to change how it functions or reacts to situations based on feedback it receives
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Learning System-
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a computer system that can simulate the functioning of a human brain
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Neural network-
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an approach to solving large, complex problems in which a number of algorithms or models change and evolve until the best one emerges
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Genetic algorithum-
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software programs and a knowledge base to perform a specific task for a person, a process, or another program
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Intelligent agent-
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a collection of software packages and tools used to develop expert systems
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Expert system shell-
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a component of an expert system that stores all relevant information, data, rules, cases, and relationships used by the expert system
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Knowledge base-
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rules that suggest certain conclusions
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If-then statements-
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a special research area in computer science that allows shades of gray and does not require everything to be simple black or white, yes or no, or true or false
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Fuzzy Logic
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a conditional statement that links given conditions to actions or outcomes
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Rule
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part of the expert system that seeks information and relationships from the knowledge base and provides answers, predictions, and suggestions the way a human expert would
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Inference Engine
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the process of starting with conclusions and working backward to the supporting facts
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Backward chaining
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the process of starting with the facts and working forward to the conclusions
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Forward chaining
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component of an expert system that allows a user or decision maker to understand how the expert system arrived at certain conclusions or result
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Explanation facility
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part of the expert system that provides a convenient and efficient means of capturing and storing all the components of the knowledge base
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Knowledge acquisition facility-
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the area of knowledge addressed by the expert system
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Domain
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the individual or group has been the expertise or knowledge someone is trying to capture in the expert system
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Domain Expert
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an individual who has training or experience in the design, development, implementation, and maintenance of an expert system
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Knowledge engineer-
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the individual or group of who uses and benefits from the expert system
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Knowledge user
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a system that enables one or more users to move and react in a computer-simulated environment
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Virtual Reality System
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