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Veterans aid and attendance The Artificial Intelligence community sought to understand human intelligence by building computer programs, which exhibited intelligent behavior. Intelligence was perceived to be a problem solving ability. Most human problems appeared to have reasoned, rather than mathematical, solutions. The diagnosis of a disease could hardly be calculated. If a patient had a group of symptoms, then she had a particular disease. But, such reasoning required prior knowledge. The programs needed to have the “knowledge” that the disease exhibited a particular group of symptoms. For the AI community, that vague knowledge residing in the minds of “Experts” was superior to text book knowledge. So they called the programs, which solved such problems, Expert Systems. back to school party ideas

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Ceramic tile trivets Expert Systems managed goal oriented problem solving tasks including diagnosis, planning, scheduling, configuration and design. One method of knowledge representation was through “If, then...” rules. When the “If” part of a rule was satisfied, then the “Then” part of the rule was concluded. These became rule based Expert Systems. But knowledge was sometimes factual and at other times, vague. Factual knowledge had clear cause to effect relationships, where clear conclusions could be drawn from concrete rules. Pain was one symptom of a disease. If the disease always exhibited pain, then pain pointed to the disease. But vague and judgmental knowledge was called heuristic knowledge. It was more of an art. The pain symptom could not mechanically point to diseases, which occasionally exhibited pain. Uncertainty did not yield concrete answers.

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