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Artificial Intelligence
(AI)
Lecture No. 1
Disciplines which form the core of AI- inner circle
Fields which draw from these disciplines- outer circle.
Robotics
NLP (Natural Language Processing)
Expert
Systems
Search,
Reasoning,
Learning
Planning
Computer
Vision
Agenda
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Intelligence
Intelligence of computer
Artificial intelligence
Intelligent computing Vs Conventional computing
Contribution of other fields to AI
History of AI
Applications of AI
References
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Intelligence?
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Can Intelligence be defined?
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Intelligence can not be defined abstractly
There are probably as many definitions of intelligence as there
are experts who study it.
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Intelligence (defination)
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from "Mainstream Science on Intelligence"
(1994), an editorial statement by fifty-two
researchers:
A
very general mental capability that, among other
things, involves the ability to reason, plan, solve
problems,
think
abstractly
(conceptually),
comprehend complex ideas, learn quickly and learn
from experience.
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(Gottfredson, L.S., 1997).
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Intelligence
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from "Intelligence: Knowns and Unknowns"
(1995), a report published by the Board of
Scientific
Affairs
of
the
American
Psychological Association:
 Individuals
differ from one another in their ability
to understand complex ideas, to adapt effectively
to the environment, to learn from experience, to
engage in various forms of reasoning, to overcome
obstacles by taking thought.
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(Neisser, 1997) and (Perloff, 1996)
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Other definitions of intelligence
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capacity for learning, reasoning, understanding, and
similar forms of mental activity; aptitude (ability) in
grasping truths, relationships, facts, meanings, etc.
the faculty(perceptual powers of the mind ) of
understanding.
knowledge of an event, circumstance, etc., received
or imparted; news; information.
the gathering or distribution of information,
especially secret information
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www. dictionary.com
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Intelligence (summary)
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Intelligence is the ability of:
 abstract
thought( Apart from a particular
case or instance)
 understanding
 communication (The activity of conveying
information)
 Reasoning (Logical thinking)
 Learning(Acquiring skill or knowledge)
 planning (Process of thinking about what to
do in the event of something happening)
 problem solving
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Intelligence of computer
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According to the British computer scientist
Alan Turing's test in (1950):
 “a
computer would deserves to be called
intelligent if it could deceive a human into
believing that it was human.”
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Artificial Intelligence?
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???
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Artificial Intelligence
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“A branch of a computer science which studies
the development of software and hardware
which simulates human intelligence”
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(Dr. Ghassan Issa)
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Artificial Intelligence
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AI is the part of computer science concerned with
designing intelligent computer systems, that is,
computer systems that exhibit the characteristics we
associate with intelligence in human behavior Understanding
languages,
 learning,
 reasoning,
 solving
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problems, and so on.
(Barr and Feigenbaum, 1981)
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Other Definitions of AI ….
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“AI is the study of how to make computer do
things at which, at the moment, people are
better”
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(Rich and Knight, 1991)
“AI is the study of idea that enable computers
to be intelligent”
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(Patrick H. Winston)
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“AI is a collection of hard problems which can
be solved by humans and other living things,
but for which we don’t have good algorithms
for solving”.
–e. g., understanding spoken natural
language, medical diagnosis, circuit
design, learning, self-adaptation,
reasoning, chess playing, proving math
theories, etc
Intelligent computing Vs Conventional
computing
Intelligent Computing
Conventional
Computing
1
Does not guarantee a
1
solution to a given problem.
Guarantees a solution to a
given problem.
2
Results may not be reliable
and consistent
2
Results are consistent and
reliable.
3
Programmer does not tell
the system how to solve the
given problem.
3
Programmer tells the
system exactly how to solve
the problem
4
Can solve a range of
problems in a given
domain.
4
Can solve only one problem
at a time in a given domain
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Intelligent computing Vs Conventional
computing …
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Conventional:
 Based
on algorithms whose instructions are stored
in memory and executed in sequential way.
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AI Computing:
 Not
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based on algorithms but based on:
Knowledge base (symbolic representation)
 Uses
reasoning and inferencing over the knowledge
base to search and perform pattern matching.
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Intelligent computing Vs Conventional
computing …
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Contributions of other disciplines to AI
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Logic, methods of reasoning, mind as physical
system,
foundations
of
learning,
language,
rationality (wisdom)
Mathematics
Formal representation and proof of algorithms,
computation,
(un)decidability,
(in)tractability,
probability
Economics
utility, decision theory
Neuroscience
how do brain process information (neuron operation)
Psychology
1- How do humans and animals think and act
2- phenomena of perception and motor control,
experimental techniques
Computer engineering building fast computers
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Control theory
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Linguistics
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Philosophy
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1- How can artifacts (objects) operate under their own
control?
2- design systems that maximize an objective
function over time.
knowledge representation, grammar
Abridged history of artificial intelligence
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1941
1943
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Boolean circuit model of brain
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1949
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1950
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first electric computer was developed
McCulloch & Pitts:
first “stored program” computer was introduced
Turing proposed his “Turing Test” for
intelligence.
1955
early chess playing programs demonstrated
1956
in Dartmouth conference birth was given to:
 "Artificial Intelligence"
1957
LISP(List
Processing)
language
by
John McCarthy at MIT
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Abridged history of artificial intelligence
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1965
1965
expert system DENDRAL started at Stanford
Robinson's complete algorithm for logical
reasoning
1966
expert system MACSYMA started at MIT
1969—79 Early development of knowledge-based systems
1970
implementation of the Prolog language
1972
expert system MYCIN developed at Stanford
1972
SHRDLU natural language robot demonstrated at
MIT
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Abridged history of artificial intelligence
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1980-1981--
AI becomes an industry
Commercial NLP system “Intellect” available
from NLP group
1986-Neural networks return to popularity
1987-AI becomes a science
1995-The emergence of intelligent agents
1995-2007 HLAI (Human Level AI):
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AI should return to its roots of striving "machines that
think, that learn”
Hays and Efros (2007)
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discuss the problem of filling in holes in a photograph
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Abridged history of artificial intelligence
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2008--Artificial General Intelligence or AGI
AGI looks for a universal algorithm for learning and acting in
any environment
(Halevy et al_ 2009)
 learning algorithm
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Applications of AI
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Game playing
General problem solving
Expert system
Natural language Processing
Computer vision
Robotics
Education
Others
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References
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Gottfredson, L.S. (1997). "Foreword to "intelligence and social policy"" Intelligence 24 (1):
1–12.
doi:10.1016/S0160-2896(97)90010-6.
http://www.udel.edu/educ/gottfredson/reprints/1997specialissue.pdf.
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Neisser, U.; Boodoo, G.; Bouchard Jr, T.J.; Boykin, A.W.; Brody, N.; Ceci, S.J.; Halpern,
D.F.; Loehlin, J.C.; Perloff, R.; Sternberg, R.J.; Others, (1998). "Intelligence: Knowns and
Unknowns". Annual Progress in Child Psychiatry and Child Development 1997.
ISBN
9780876308707.
http://books.google.com/?id=gLWnmVbKdLwC&pg=PA95&dq=Intelligence:+Knowns+and
+unknowns.
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Perloff, R.; Sternberg, R.J.; Urbina, S. (1996). "Intelligence: knowns and unknowns".
American Psychologist 51.
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Dr. Ghassan Issa, Artificial intelligence, retrieved from: http://www.uop.edu.jo/issa/ai/aipart1.htm, retrieved date: 04 Oct, 2011.
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References
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Crash Course in Artificial Intelligence and Expert systems by Louise E.
Frenzel.
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Chapter No.1
Artificial Intelligence - A Modern Approach 3rd ed - S. Russell, P.
Norvig (Prentice-Hall, 2010) WW
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Chapter No.1
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The end
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