(14th-February-2020)
About 400 years ago people started to write about the nature of thought and reason.
Hobbes (1588-1679), who has been described by Haugeland (1985), as the "Grandfather of AI," espoused the position that thinking was symbolic reasoning like talking out loud or working out an answer with pen and paper.
The idea of symbolic reasoning was further developed by Descartes (1596-1650), Pascal (1623-1662), Spinoza (1632-1677), Leibniz (1646-1716), and others who were pioneers in the philosophy of mind.
The first general-purpose computer designed (but not built until 1991, at the Science Museum of London) was the Analytical Engine by Babbage (1792-1871). In the early part of the 20th century, there was much work done on understanding computation.
Turing machine by Alan Turing (1912-1954), a theoretical machine that writes symbols on an infinitely long tape, and the lambda calculus of Church (1903-1995), which is a mathematical formalism for rewriting formulas.
During the 1960s and 1970s, success was had in building natural language understanding systems in limited domains. STUDENT program of Daniel Bobrow (1967) could solve high school algebra problems expressed in natural language. [Winograd (1972)]'s SHROUD system could, using restricted natural language, discuss and carry out tasks in a simulated blocks world. CHAT-80 [Warren and Pereira (1982)] could answer geographical questions placed to it in natural language
• AI is a very young discipline. Other disciplines as diverse as philosophy, neurobiology, evolutionary biology, psychology, economics, political science, sociology, anthropology, control engineering, and many more have been studying intelligence much longer.
• AI can be seen as coming under the umbrella of cognitive science. Cognitive science links various disciplines that study cognition and reasoning, from psychology to linguistics to anthropology to neuroscience. AI distinguishes itself within cognitive science by providing tools to build intelligence rather than just studying the external behavior of intelligent agents or dissecting the inner workings of intelligent systems..
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