Transcript 1. A Brief History of AI - Computing Science

A Brief History of AI
Fall 2013
COMP3710 Artificial Intelligence
Computing Science
Thompson Rivers University
Course Outline
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Part I – Introduction to Artificial Intelligence
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A Brief History of Artificial Intelligence
Uses and Limitations
Part II – Classical Artificial Intelligence
Part III – Machine Learning
Part IV – Advanced Topics
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Learning Outcomes
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Define what AI is
Distinguish strong AI and weak AI
Distinguish strong methods and weak methods
Explain what the Turing test is
List important study areas in AI
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Reference
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Chapter 1. A Brief History of Artificial Intelligence
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Unit Outline
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What is AI?
Strong methods and weak methods
Alan Turing and the 1950s
The 1960s to the 1990s
...
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1.2 What is AI
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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.
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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1.2 What is AI - cont
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Strong AI
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Weak AI:
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One can create a computer that can literally think and is conscious in the
same way that a human is conscious.
This is the view that a sufficiently programmed computer would actually
be intelligent and would think in the same way that a human does.
Intelligent behavior can be modeled and used by computers to solve
complex problems.
This is the use of methods modeled on intelligent behavior to make
computers more efficient at solving problems.
What is your opinion?
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1.3 Strong Methods and Weak Methods
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Strong method problem solving depends on a system being given a
great deal of knowledge about its world and the problems that is might
encounter.
Strong methods use knowledge about the world to solve problems.
Weak methods use systems such as logic, automated reasoning, and
other general structures that can be applied to a wide range of
problems but that do not necessarily incorporate any real knowledge
about the world of the problem.
Weak methods use logic and other symbolic systems.
Are strong methods enough to implement an intelligent system?
Are weak methods enough to implement an intelligent system?
Strong method systems rely on weak methods, as knowledge is useless
without a way to handle that knowledge.
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1.5 Alan Turing and the 1950s
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Alan Turing (1950) "Computing machinery and intelligence":
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"Can machines think?"  "Can machines behave intelligently?"
The Turing Test was designed as a way to judge the success or otherwise
of an attempt to produce a thinking computer.
Required capabilities???
• Natural language processing
• Knowledge representation
• Automated reasoning
• Machine learning
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Predicted that by 2000, a machine might have a 30% chance of fooling a
lay person for 5 minutes
What do you think?
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But no system has yet passed the Turing Test.
Is the Turing Test enough to test whether a given system is intelligent?
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1.5 Alan Turing and the 1950s - cont
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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
at a conference.
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1.6 The 1960s to the 1990s
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Since the 1950s, a great deal of the original optimism has gone out of
AI and has been replaced with a degree of realism.
Areas of particular importance
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Machine learning
Multi-agent systems
Artificial life
Computer vision
Planning
Playing games
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