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  Report: Slave and Expert Systems

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 WORLD-INFOSTRUCTURE > SLAVE AND EXPERT SYSTEMS > 1950: THE TURING TEST
  1950: The Turing Test


Alan Turing, an English mathematician and logician, advocated the theory that eventually computers could be created that would be capable of human thought. To cut through the long philosophical debate about exactly how to define thinking he proposed the "imitation game" (1950), now known as Turing test. His test consisted of a person asking questions via keyboard to both a person and an intelligent machine within a fixed time frame. After a series of tests the computers success at "thinking" could be measured by its probability of being misidentified as the human subject. Still today Turing's papers on the subject are widely acknowledged as the foundation of research in artificial intelligence.




browse Report:
Slave and Expert Systems
    Introduction: The Substitution of Human Faculties with Technology: Early Tools
 ...
-3   The 19th Century: First Programmable Computing Devices
-2   1913: Henry Ford and the Assembly Line
-1   1940s - Early 1950s: First Generation Computers
0   1950: The Turing Test
+1   1940s - 1950s: The Development of Early Robotics Technology
+2   1950s: The Beginnings of Artificial Intelligence (AI) Research
+3   Late 1950s - Early 1960s: Second Generation Computers
     ...
1980s: Artificial Intelligence (AI) - From Lab to Life
 INDEX CARD     RESEARCH MATRIX 
Expert system
Expert systems are advanced computer programs that mimic the knowledge and reasoning capabilities of an expert in a particular discipline. Their creators strive to clone the expertise of one or several human specialists to develop a tool that can be used by the layman to solve difficult or ambiguous problems. Expert systems differ from conventional computer programs as they combine facts with rules that state relations between the facts to achieve a crude form of reasoning analogous to artificial intelligence. The three main elements of expert systems are: (1) an interface which allows interaction between the system and the user, (2) a database (also called the knowledge base) which consists of axioms and rules, and (3) the inference engine, a computer program that executes the inference-making process. The disadvantage of rule-based expert systems is that they cannot handle unanticipated events, as every condition that may be encountered must be described by a rule. They also remain limited to narrow problem domains such as troubleshooting malfunctioning equipment or medical image interpretation, but still have the advantage of being much lower in costs compared with paying an expert or a team of specialists.