Download 1 - Jordan University of Science and Technology

Artificial Intelligence
Hassan Najadat
Jordan University of Science &
Technology
CS 362
SLIDE 1
Outline
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Course Overview
What is AI ?
A brief history
The state of the art
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Course Overview
• Intelligent agent
• Problem Solving
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Solving problems by searching
Informed Search and Exploration
Constraint Satisfaction Problems
Adversarial Search
• Logical system
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Logical Agent
First Order Logic
Inference in First-Order Logic
Knowledge Representation
• Learning from Observations
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SLIDE 3
What is AI ?
“Like People”
“Rationally”
Think
Cognitive
Science
Laws of
Thought
Act
Turing Test
Rational Agents
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SLIDE 4
What is AI ?
Systems that think like humans
Systems that think rationality
``The exciting new effort to make
computers think ... machines with minds,
in the full and literal sense'' (Haugeland,
1985)
``The automation of activities that we
associate with human thinking, activities
such as decision-making, problem
solving, learning ...'' (Bellman, 1978)
``The study of mental faculties through the
use of computational models'' (Charniak
and McDermott, 1985)
``The study of the computations that make
it possible to perceive, reason, and act''
(Winston, 1992)
Systems that act like humans
Systems that act like rationality
``The art of creating machines that
perform functions that require intelligence
when performed by people'' (Kurzweil,
1990)
``The study of how to make computers do
things at which, at the moment, people
are better'' (Rich and Knight, 1991)
``A field of study that seeks to explain and
emulate intelligent behavior in terms of
computational processes'' (Schalkoff,
1990)
``The branch of computer science that is
concerned with the automation of
intelligent behavior'' (Luger and
Stubblefield, 1993)
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SLIDE 5
Acting humanly: The Turing Test approach
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The Turing Test, proposed by Alan Turing (Turing, 1950), was
designed to provide a satisfactory operational definition of
intelligence.
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The computer would need to possess the following
capabilities:
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Natural language processing to enable it to communicate successfully in
English (or some other human language);
Knowledge representation to store information provided before or during the
interrogation;
Automated reasoning to use the stored information to answer questions and
to draw new conclusions;
Machine learning to adapt to new circumstances and to detect and
extrapolate patterns.
To pass the total Turing Test, the computer will need
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Computer Vision
Robotics
SLIDE 6
Example
Natural Language (NL) Processing
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noun
verb
determiner
adjective
adverb
pronoun
s --> det, noun, verb, det, noun.
a better version
– s --> np, verb.
s --> np, verb, np.
np --> det, adj*, noun.
np --> proper-name.
np --> pronoun.
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SLIDE 7
Thinking humanly: The cognitive modeling approach
- Program thinks like a human ..!
We need to get inside the actual workings of human minds.
There are two ways:
– through introspection--trying to catch our own thoughts as they
go by—
– or through psychological experiments.
• GPS -``General Problem Solver''
– (GPS) A procedure and program developed by Allen Newell, J.
C. Shaw, and Herbert Simon.
– GPS attains an objective by using recursive search and by
applying rules to generate the alternatives at each branch in the
recursive expansion of possible sequences.
– GPS uses a procedure to measure the "distance" from the goal.
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SLIDE 8
Thinking rationality: The Logical approach
• Ensure that all actions performed by computer are
justifiable (“rational”)
Facts and Rules
in Formal Logic
Theorem Prover
• Rational = Conclusions are provable from inputs and
prior knowledge
• Problems:
– Representation of informal knowledge is difficulty
– Hard to define “provable” plausible reasoning
– Combinatorial explosion: Not enough time or space to prove
desired conclusions.
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SLIDE 9
Acting rationally: The rational agent approach
• Rational behavior : doing the right thing ( that which is
expected to maximize goal achievement, given the available
information).
• Agent
• Program
• Agent and Program
• Rational Agent is one that acts to achieve the best outcomes
or, when there is uncertainty, the best expected outcome.
Rational agents do the best they can
given their resources
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SLIDE 10
Rational Agents
very few resources
no thought
“reflexes”
lots of resources
limited,
approximate
reasoning
Careful, deliberate
reasoning
• Adjust amount of reasoning according to
available resources and importance of
the result
• This is one thing that makes AI hard
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SLIDE 13
Areas of Study in AI
• Reasoning, optimization, resource allocation
– planning, scheduling, real-time problem solving,
intelligent assistants, internet agents
• Natural Language Processing
– information retrieval, summarization, understanding,
generation, translation
• Vision
– image analysis, recognition, scene understanding
• Robotics
– grasping/manipulation, locomotion, motion planning,
mapping
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SLIDE 14
Where are we now?
• SKICAT: a system for automatically classifying the
terabytes of data from space telescopes and identifying
interesting objects in the sky. 94% classification
accuracy, exceeds human abilities.
• Deep Blue: the first computer program to defeat
champion Garry Kasparov.
• Pegasus: a speech understanding program that is a
travel agent (1-877-LCS-TALK).
• Jupiter: a weather information system (1-888-573-TALK)
• HipNav: a robot hip-replacement surgeon.
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Where are we now?
• Navlab: a Ford escort that steered itself from Washington
DC to San Diego 98% of the way on its own!
• google news: autonomous AI system that assembles
“live” newspaper
• DS1: a NASA spacecraft that did an autonomous flyby
an asteroid.
• Credit card fraud detection and loan approval
• Search engines: www.citeseer.com, automatic
classification and indexing of research papers.
• Proverb: solves NYT puzzles as well as the best
humans.
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SLIDE 16
Surprises in AI research
• Tasks difficult for humans have turned out to be
“easy”
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Chess
Checkers, Othello, Backgammon
Logistics planning
Airline scheduling
Fraud detection
Sorting mail
Proving theorems
Crossword puzzles
SLIDE 17
Surprises in AI research
• Tasks easy for humans have turned out to be
hard.
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Speech recognition
Face recognition
Composing music/art
Autonomous navigation
Motor activities (walking)
Language understanding
Common sense reasoning (example: how many legs
does a fish have?)
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