Chapter 1
A Brief History of Artificial
Intelligence
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Chapter 1 Contents
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What is Artificial Intelligence?
Strong AI and Weak AI
Strong Methods and Weak Methods
From Aristotle to Babbage
Alan Turing and the 1950s
The 1960s to the 1990s
Philosophy
Linguistics
Human Psychology and Biology
Prolog
LISP
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What is Artificial Intelligence? (1)
A more difficult question is: What is
intelligence?
 This question has puzzled
philosophers, biologists and
psychologists for centuries.
 Artificial Intelligence is easier to
define, although there is no standard,
accepted definition.
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What is Artificial Intelligence? (2)
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A simple definition might be as follows:
Artificial intelligence is the study of systems that
act in a way that to any observer would appear to
be intelligent.
In fact, Artificial Intelligence techniques are often
used to solve relatively simple problems, or
complex problems that are internal to more
complex systems.
This may lead us to another definition of Artificial
Intelligence, as follows:
Artificial Intelligence involves using methods
based on the intelligent behavior of humans and
other animals to solve complex problems.
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Strong AI and Weak AI
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There are two entirely different schools of
Artificial Intelligence:
Strong AI:
 This is the view that a sufficiently programmed computer
would actually be intelligent and would think in the same way
that a human does.
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Weak AI:
 This is the use of methods modeled on intelligent behavior to
make computers more efficient at solving problems.
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This course is concerned with Weak AI.
Strong AI is currently the stuff of science fiction,
although there are many that believe that
machines will indeed be capable of real thought at
some point in the future.
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Strong Methods and Weak Methods
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Not to be confused with Strong AI and Weak AI.
Strong methods use knowledge about the world
to solve problems.
Weak methods use logic and other symbolic
systems.
Strong method systems rely on weak methods,
as knowledge is useless without a way to
handle that knowledge.
Weak methods are in no way inferior to strong
methods – they simply do not employ world
knowledge.
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From Aristotle to Babbage
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Aristotle’s study of logic was vital to the study of logic
which is an important part of Artificial Intelligence.
Aristotle’s work was expanded on by the likes of Peter
Abelard, Gottfried Leibniz and George Boole.
Charles Babbage was the inventor of the first
computer –the Analytic Engine, in the 19th Century.
This computer was not actually built until the 20th
Century, but Babbage’s work provided an important
basis for the early work in Artificial Intelligence.
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Alan Turing and the 1950s
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Alan Turing is often seen as the father of Artificial
Intelligence.
He invented the Turing Test, designed to determine if a
computer system can be called an artificial intelligence or
not, based on whether it can fool a human into thinking it
is human too.
No system has yet passed the Turing Test.
Around this time, in the 1950’s, systems were being
developed that could play checkers, engage in
conversation and solve other problems.
The term Artificial Intelligence was coined in 1956 by John
McCarthy.
Machine translation was considered to be a solvable
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problem.
The 1960s to the 1990s
During this time, the optimism of the
1950s was replaced with realism.
 Artificial Intelligence replaced as its
goal the building of an intelligent
robot with the goal of using
heuristics and other techniques to
solve complex problems.
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Philosophy
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Philosophy provides an important
background to a study of AI.
Descartes’ dualism described a universe
consisting of two separate things: mind
and matter.
Descartes believed that humans
possessed minds, but that animals were
simply biological machines.
The work of Aristotle, Descartes and more
recently Daniel Dennett are worth
studying.
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Linguistics
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For computers to interact with humans
properly, they need to understand human
language.
Noam Chomsky’s work on grammars has
informed the study of natural language
processing (NLP).
Knowledge representation which is
fundamental to AI is essential to
understanding language.
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Human Psychology and Biology
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While most AI techniques do not map
neatly onto real biological systems, some,
such as neural networks, do.
Cognitive Psychology has many links with
AI: It involves the idea that the human
brain uses processing methods on
knowledge to solve problems.
This contrasts with behaviorism, which is
the view that behavior is linked directly to
stimuli.
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Prolog
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PROLOG (PROgramming in LOGic):
 A language designed to build databases of facts and
rules, and then to have the system answer questions by
a process of logical deduction using the facts and rules
in the database.
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Facts:
tasty (cheese).
made_from (cheese, milk).
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Rules:
contains (X, Y) :- made_from (X, Z), contains
(Z, Y).
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Prolog is not an efficient language like C++, but it is
the language of choice when building systems based
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on logic.
LISP
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LISP (LISt Programming):
 A language which more closely resembles the
imperative programming languages such as
C++ than does PROLOG.
 As its name suggests LISP is based around
handling of lists of data. A list in LISP is
contained within brackets, such as:
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(A B C)
Lists represent data and also programs,
meaning LISP programs can manipulate other
programs, and it is even possible to write self14
modifying LISP programs.