Defining AI
The phrase AI, which was coined by John McCarthy [1] three decades ago,
evades a concise and formal definition to date. One representative definition is
pivoted around the comparison of intelligence of computing machines with
human beings [11]. Another definition is concerned with the performance of
machines which ?historically have been judged to lie within the domain of
intelligence? [17], [35]. None of these definitions or the like have been
universally accepted, perhaps because of their references to the word
?intelligence?, which at present is an abstract and immeasurable quantity. A
better definition of AI, therefore, calls for formalization of the term
?intelligence?. Psychologist and Cognitive theorists are of the opinion that
intelligence helps in identifying the right piece of knowledge at the appropriate
instances of decision making [27], [14].The phrase ?AI? thus can be def-
ined as the simulation of human intelligence on a machine, so as to make
the machine efficient to identify and use the right piece of
?Knowledge? at a given step of solving a problem. A system capable of
planning and executing the right task at the right time is generally called
rational [36]. Thus, AI alternatively may be stated as a subject dealing with
computational models that can think and act rationally [18]1, [47]2, [37]3,
[6]4. A common question then naturally arises: Does rational thinking and
acting include all possible characteristics of an intelligent system? If so, how
does it represent behavioral intelligence such as machine learning, perception
and planning? A little thinking, however, reveals that a system that can reason
well must be a successful planner, as planning in many circumstances is part
of a reasoning process. Further, a system can act rationally only after
acquiring adequate knowledge from the real world. So, perception that stands
for building up of knowledge from real world information is a prerequisite
feature for rational actions. One step further thinking envisages that a
machine without learning capability cannot possess perception. The rational
action of an agent (actor), thus, calls for possession of all the elementary
characteristics of intelligence. Relating AI with the computational models
capable of thinking and acting rationally, therefore, has a pragmatic
significance.
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