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ECE457 Applied Artificial Intelligence
R. Khoury (2007)
Page 1
Introduction to AI
ECE457 Applied Artificial Intelligence
Spring 2007
Lecture #1
Outline
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What is an AI?
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Russell & Norvig, chapter 1
Agents
Environments
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Russell & Norvig, chapter 2
ECE457 Applied Artificial Intelligence
R. Khoury (2007)
Page 3
Artificial Intelligence
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Artificial intelligence is all around us
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Computer players in
video games
Robotics
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Expert systems
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Assembly-line robots,
auto-pilot, Mars
exploration robots,
RoboCup, etc.
Medical diagnostics,
business advice,
technical help, etc.
Natural language

Spam filtering,
translation, document
summarization, etc.
ECE457 Applied Artificial Intelligence
R. Khoury (2007)
Page 4
What is an AI?

Systems that…
Humanly
Neural
Think
networks
ELIZA
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Rationally
Theorem
proving
Deep Blue
Act
Rationality vs. Humans: emotions, instincts,
etc.
Thinking vs. acting: Turing test vs. Searle’s
Chinese room
Engineers (and this course) focus mostly on
rational systems
ECE457 Applied Artificial Intelligence
R. Khoury (2007)
Page 5
Act Rationally
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Perceive the environment, and act so as to
achieve one’s goal
Not necessary to do the best action
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There’s not always an absolutely best action
There’s not always time to find the best action
An action that’s good enough can be acceptable
Example: Game playing
Sample approach: Tree-searching strategies
Problem: Choosing what to do given the
constraints
ECE457 Applied Artificial Intelligence
R. Khoury (2007)
Page 6
Think Rationally

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Uses logic to reach a decision or goal
via logical inferences
Example: Theorem proving
Sample approach: First-order logic
Problems:

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Informal knowledge
Uncertainty
Search space
ECE457 Applied Artificial Intelligence
R. Khoury (2007)
Page 7
Think Rationally
1.
2.
3.
X = Y/Z  XZ = Y
X=Y
X+Z=Y+Z
X*Y+X*Z
X * (Y + Z)
a.
b.
c.
d.
e.
4.
5.
6.
b² = AH * c
a² = BH * c
a² + b² =
BH * c + AH * c
a² + b² =
c * (AH + BH)
a² + b² = c²
b/c = AH/b
a/c = BH/a
AH + BH = c
ECE457 Applied Artificial Intelligence
R. Khoury (2007)
Page 8
Act Humanly
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“Turing-test” AI
Improve human-machine interactions
up to human-human level
Drawbacks:

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In some cases, requires dumbing down the
AI
Lots of man-made devices work well
because they don’t imitate nature
ECE457 Applied Artificial Intelligence
R. Khoury (2007)
Page 9
Think Humanly

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Cognitive science
Neural networks
Helps in other fields
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Computer vision
Natural language processing
ECE457 Applied Artificial Intelligence
R. Khoury (2007)
Page 10
Rational Agents

An agent has

A rational agent has
an agent program
that allows it to do
the right action given
its precepts
ECE457 Applied Artificial Intelligence
Sensors
Actions

Percepts
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Sensors to perceive
its environment
Actuators to act upon
its environment
Environment
Actuators
Agent
Program
R. Khoury (2007)
Page 11
Properties of the Environment
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Fully observable vs. partially observable
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Deterministic vs. stochastic vs. strategic
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Translation vs. driving vs. chess with timer
Discrete vs. continuous
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Face recognition vs. chess
Static vs. dynamic vs. semi-dynamic
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Sudoku vs. Yahtzee vs. chess
Episodic vs. sequential
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Chess vs. Stratego
Chess vs. driving
Single agent vs. cooperative vs. competitive

Sudoku vs. sport team vs. chess
ECE457 Applied Artificial Intelligence
R. Khoury (2007)
Page 12
Types of Agents
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Simple reflex agent
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Model-based agent
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Considers what will happen given its actions
Utility-based agent
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Keeps track of perception history
Goal-based agent
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Selects action based only on current perception of
the environment
Adds the ability to choose between
conflicting/uncertain goals
Learning agent

Adds the ability to learn from its experiences
ECE457 Applied Artificial Intelligence
R. Khoury (2007)
Page 13