The Definitions of Artificial Intelligence
Artificial intelligence can be defined as follows:
- The study of mental faculties through the use of computational models. CHARNLAK & MCDERMOTT 1985
- The exciting new effort to make computers think…machines with mind, in the full and literal sense. HAUGELAND 1985
- The art of creating machines that perform functions that require intelligence when performed by people. KURZWEIL 1990
- A field of study that seeks to explain and emulate intelligent behaviour in terms of computational processes. SCHALKOFF 1990
- The study of how to make computers do things at which, at the moment, people are better. RICH & KNIGHT 2003
- The study of the computations that make it possible to perceive, reason, and act. WINSTON 1992
- The branch of computer science that is concerned with the automation of intelligent behaviour. LUGER & STUBBLEFIELD 1993
According to these definitions, computer systems can be classified into the following categories.
- Systems that act like humans
- System that think like humans
- Systems that think rationally
- System that act rationally
1. System that act like humans
The Turing test, proposed by Alan Turing (1950), was designed to provide a satisfactory operational definition of intelligence, Turing defined intelligent behaviour as the ability to achieve human level performance in all cognitive tasks sufficient to fool an interrogator. Roughly, the test he proposed is that a computer should be interrogated by a human via teletype; it will pass the test if the interrogator cannot tell if there is a computer or a human at the other end.
2. System that think like humans
Several important programming projects were started during the late 1950s. Among them was the General Problem Solver (GPS). Newll and Simon, who developed the GPS in 1961, were not content to have their program correctly solve problems. They were more concerned with comparing the trace of its reasoning steps to that human subjects solving the same problem ( Yazdani & Narayanana 1985). This is in contrast to the ideas of other researchers of the same time (Wang 1960), who were concerned with getting the right answers regardless of how human might do it. The interdisciplinary field of cognitive science brings together computer models on AI and experimental techniques from psychology to try and construct precise and testable theories of the working of the human mind.
Turing’s criterion to warrant such a blurring of distinction was presented in the form of a test called the ‘imitation game’, which is new way to solve the problem-“Can a machine think?”. Dr Alan Turing compares the computer to a human to decide whether a machine can think. The game is played with three people: a man (A), a woman (B), and an interrogator (X) of either sex. A and B stay in room apart from X, who does not know which of A and B is the man and which is the woman. His/her objective is to determine the sex of A and B correctly by asking them questions. X cannot see or hear A or B but passes messages through an intermediary, which could be an electronic mail system or another person. As they respond to questions, A and B complete with each other to confuse the interrogator. X finally give his verdict based on their responses. Now the game is played by replacing either A or B with a machine and the original question is replaced by the following questions:”What will happen when a machine takes the part of A in this game?”. ” Will the interrogator decide wrongly as often when the game is played like this as he does when the game is played between a man and a woman?”.
If the answer to the second question is positive, the machine passes the Turing test and, based on this particular criterion, can think (Tanimoto 1987). However, in practice, the outcome of such a test would probably depend heavily on the humans involved as well as the machine.
In 1973, Colby, Hilf, Weber, and Kramer published the results of their Turing like indistinguishability test with their PARRY program. This program is a computer simulation that exhibits behaviour similar to that of human paranoia patients. The physician who judged the computer versus the patients failed to distinguish the computer accurately, and it is claimed that the test had succeeded.
3. Systems that think rationally
The Greek philosopher Aristotle was one of the first to attempt to codify ” right thinking “. His famous syllogisms provided for argument structures that always give correct conclusions given premises, For example, ” X is a man, all men are mortal; therefore X is mortal.” These laws of thought were supposed to govern the operation of the mind, and initiated the field of logic.
4. Systems that act rationally
In the ” laws of thought ” approach to AI, the whole emphasis was on correct inference. Making correct inferences is sometimes part of being a rational agent, because one way to act rationally is to reason logically to the conclusion that a given action will achieve ones’ s goal, and then to act on the conclusion. On the other hand, correct inference is not all rationality, because there are often situations where there is no provably correct thing to do, yet something must still done, For example, pulling one’ s hand off of a hot stove is a reflex action that is more successful that a slower action taken after careful deliberation.
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