Report: Slave and Expert Systems

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  1960s - 1970s: Increased Research in Artificial Intelligence (AI)

During the cold war the U.S. tried to ensure that it would stay ahead of the Soviet Union in technological advancements. Therefore in 1963 the Defense Advanced Research Projects Agency (DARPA) granted the Massachusetts Institute of Technology (MIT) U.S.$ 2.2 million for research in machine-aided cognition (artificial intelligence). The major effect of the project was an increase in the pace of AI research and a continuation of funding.

In the 1960s and 1970s a multitude of AI programs were developed, most notably SHRDLU. Headed by Marvin Minsky the MIT's research team showed, that when confined to a small subject matter, computer programs could solve spatial and logic problems. Other progresses in the field of AI at the time were: the proposal of new theories about machine vision by David Marr, Marvin Minsky's frame theory, the PROLOGUE language (1972) and the development of expert systems.

browse Report:
Slave and Expert Systems
    Introduction: The Substitution of Human Faculties with Technology: Early Tools
-3   Late 1950s - Early 1960s: Second Generation Computers
-2   1961: Installation of the First Industrial Robot
-1   Late 1960s - Early 1970s: Third Generation Computers
0   1960s - 1970s: Increased Research in Artificial Intelligence (AI)
+1   1960s - 1970s: Expert Systems Gain Attendance
+2   1970s: Computer-Integrated Manufacturing (CIM)
+3   Late 1970s - Present: Fourth Generation Computers
+4   1980s: Artificial Intelligence (AI) - From Lab to Life
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.