1. Artificial Intelligence Introduction to Artificial Intelligence
Dr. Shahriar Bijani
Shahed University
Spring 2017

2. Outline Course overview What is AI? A brief history
Introduction to AI
Course overview
What is AI?
A brief history
Predictions and Reality
Shahed University, Spring 2017

3. Course overview Introduction and Agents (chapters 1,2)
Introduction to AI
Introduction and Agents (chapters 1,2)
Search (chapters 3,4,5,6)
Logic (chapters 7,8,9)
Knowledge Representation (chapter 10)
Planning (chapters 11,12)
Uncertainty (chapters 13,14)
Learning (chapters 18,20)
Natural Language Processing (chapter 22,23)
Other Topics (Neural Nets, ….)
Shahed University, Spring 2017

4. Found on the Web … Intelligent behavior Computer Humans
Introduction to AI
AI is the reproduction of the methods of human reasoning or perception
Using computational models to simulate intelligent (human) behavior and processes
AI is the study of mental abilities through the use computational methods
Intelligent
behavior
Humans
Computer
Shahed University, Spring 2017

5. What is AI?
Introduction to AI
Discipline that systematizes and automates intellectual tasks to create machines that:
Act like humans
Act rationally
Think like humans
Think rationally
Shahed University, Spring 2017

6. Act Like Humans
Introduction to AI
The goal of AI is to create computer systems that perform functions that are assumed to require intelligence when done by humans
 Methodology: Take a task at which people are better, e.g.:
Prove a theorem
Play chess
Plan a surgical operation
Diagnose a disease
Navigate in a building
and make a computer do it
Shahed University, Spring 2017

7. Act Like Humans : Turing Test
Introduction to AI
Alan Turing (1950) "Computing machinery and intelligence":
"Can machines think?"  "Can machines behave intelligently?"
Operational test for intelligent behavior: the simulation game
The computer is asked questions by a human interviewer. It passes the test if the interviewer or cannot tell whether the responses come from a person
Shahed University, Spring 2017

8. Act Like Humans : Turing Test
Introduction to AI
Required capabilities: natural language processing, knowledge representation, automated reasoning, learning
No physical interaction
total Turing Test, needs computer vision & robotics
Shahed University, Spring 2017
What does it say about the interrogator’s own intelligence?
Chinese Room (J. Searle)

9. What is AI?
Introduction to AI
Discipline that systematizes and automates intellectual tasks to create machines that:
Act like humans
Act rationally
Think like humans
Think rationally
Shahed University, Spring 2017

10. Thinking humanly: cognitive modeling
Introduction to AI
How the computer performs functions does matter
Comparison of the traces of the reasoning steps (cognitive science)
1960s "cognitive revolution": information-processing psychology
Cognitive science: computer models (from AI) + experiments from Psychology
Requires scientific theories of internal activities of the brain, by:
1) Predicting and testing behavior of human subjects (top-down)
or 2) Direct identification from neurological data (bottom-up)
Both approaches (roughly, Cognitive Science and Cognitive Neuroscience) are now distinct from AI
But, do we want to duplicate human imperfections?
Shahed University, Spring 2017

11. Discourse on the Method, by Descartes (1598-1650)
Introduction to AI
If there were machines which bore a resemblance to our bodies and imitated our actions as closely as possible for all practical purposes, we should still have two very certain means of recognizing that they were not real men. The first is that they could never use words, or put together signs, as we do in order to declare our thoughts to others… Secondly, even though some machines might do some things as well as we do them, or perhaps even better, they would inevitably fail in others, which would reveal that they are acting not from understanding, …
Shahed University, Spring 2017

12. Discourse on the Method, by Descartes (1598-1650)
Introduction to AI
If there were machines which bore a resemblance to our bodies and imitated our actions as closely as possible for all practical purposes, we should still have two very certain means of recognizing that they were not real men. The first is that they could never use words, or put together signs, as we do in order to declare our thoughts to others… Secondly, even though some machines might do some things as well as we do them, or perhaps even better, they would inevitably fail in others, which would reveal that they are acting not from understanding, …
Shahed University, Spring 2017

13. Discourse on the Method, by Descartes (1598-1650)
Introduction to AI
If there were machines which bore a resemblance to our bodies and imitated our actions as closely as possible for all practical purposes, we should still have two very certain means of recognizing that they were not real men. The first is that they could never use words, or put together signs, as we do in order to declare our thoughts to others… Secondly, even though some machines might do some things as well as we do them, or perhaps even better, they would inevitably fail in others, which would reveal that they are acting not from understanding, …
Shahed University, Spring 2017

14. What is AI?
Introduction to AI
Discipline that systematizes and automates intellectual tasks to create machines that:
Act like humans
Act rationally
Think like humans
Think rationally
Shahed University, Spring 2017

15. Thinking rationally: "laws of thought"
Introduction to AI
Aristotle: what are correct arguments/thought processes?
Logicians developed various forms of logic: notation and rules of derivation for thoughts;
By 1965, programs existed that could solve any problem described in logical notation.
Problems:
It is not easy to state informal knowledge in the formal terms required by logical notation (particularly when it is less than 100% certain).
There is a big difference between being able to solve a problem "in principle" and doing so in practice.
Shahed University, Spring 2017

16. What is AI?
Introduction to AI
Discipline that systematizes and automates intellectual tasks to create machines that:
Act like humans
Act rationally
Think like humans
Think rationally
Shahed University, Spring 2017

17. Acting rationally: rational agent
Introduction to AI
Rational behavior: doing the right thing
The right thing: that which is expected to maximize goal achievement, given the available information
Doesn't necessarily involve thinking – e.g., blinking reflex – but thinking should be in the service of rational action
Shahed University, Spring 2017

18. Rational agents An agent is an entity that perceives and acts
Introduction to AI
An agent is an entity that perceives and acts
This course is about designing rational agents
Abstractly, an agent is a function from percept histories to actions:
[f: P*  A]
For any given class of environments and tasks, we seek the agent (or class of agents) with the best performance
computational limitations make perfect rationality unachievable  design best program for given machine resources
Shahed University, Spring 2017
Agent attribute vs. program: operating under autonomous control, perceiving their environment, persisting over a prolonged time period, adapting to change & being capable of taking on another’s goals.

19. AI prehistory
Introduction to AI
Philosophy Logic, methods of reasoning, mind as physical system foundations of learning, language, rationality
Mathematics Formal representation and proof algorithms, computation, (un)decidability, (in)tractability, probability
Economics utility, decision theory
Neuroscience physical substrate for mental activity
Psychology phenomena of perception and motor control, experimental techniques
Computer building fast computers engineering
Control theory design systems that maximize an objective function over time
Linguistics knowledge representation, grammar
Shahed University, Spring 2017

20. A Short history of AI 1940-1950: Early days
1943: McCulloch & Pitts: Boolean circuit model of brain
1950: Turing's “Computing Machinery and Intelligence”
1950—70: Excitement: Look, Ma, no hands!
1950s: Early AI programs, including Samuel's checkers program, Newell & Simon's Logic Theorist, Gelernter's Geometry Engine
1956: Dartmouth meeting: “Artificial Intelligence” adopted
1965: Robinson's complete algorithm for logical reasoning
1970—90: Knowledge-based approaches
1969—79: Early development of knowledge-based systems
1980—88: Expert systems industry booms
1988—93: Expert systems industry collapse: “AI Winter”
1990—: Statistical approaches
Reappearance of probability, focus on uncertainty
General increase in technical depth
Agents and learning systems… “AI Spring”?
2000—: Human-level AI back on the agenda
MT was a Million dollar computer with less computation than your phone

21. Predictions and Reality … (1/3)
Introduction to AI
In the 60’s, a famous AI professor from MIT said: “At the end of the summer, we will have developed an electronic eye”
Up to now, there is still no general computer vision system capable of understanding complex dynamic scenes
But computer systems routinely perform road traffic monitoring, facial recognition, medical image analysis, part inspection, motion capture, …
Shahed University, Spring 2017

22. Predictions and Reality … (2/3)
Introduction to AI
In 1958, Herbert Simon (CMU) predicted that within 10 years a computer would be Chess champion
This prediction became true in 1998
AI techniques (search, planning, probabilistic reasoning) are used in many video games
Shahed University, Spring 2017

23. Predictions and Reality … (3/3)
Introduction to AI
In the 70’s, many believed that computer-controlled robots would soon be everywhere from manufacturing plants to home
Shahed University, Spring 2017

24. Predictions and Reality … (3/3)
Introduction to AI
In the 70’s, many believed that computer-controlled robots would soon be everywhere from manufacturing plants to home
Today, some industries (automobile, electronics) are highly robotized, but home robots are still a thing of the future
Shahed University, Spring 2017

25. Predictions and Reality … (3/3)
Introduction to AI
In the 70’s, many believed that computer-controlled robots would soon be everywhere from manufacturing plants to home
Today, some industries (automobile, electronics) are highly robotized, but home robots are still a thing of the future
But robots have rolled (are rolling) on Mars, fly autonomously,
Shahed University, Spring 2017

26. Predictions and Reality … (3/3)
Introduction to AI
In the 70’s, many believed that computer-controlled robots would soon be everywhere from manufacturing plants to home
Today, some industries (automobile, electronics) are highly robotized, but home robots are still a thing of the future
But robots have rolled (are rolling) on Mars, fly autonomously, while others perform brain and heart surgery …
Shahed University, Spring 2017

27. Predictions and Reality … (3/3)
Introduction to AI
In the 70’s, many believed that computer-controlled robots would soon be everywhere from manufacturing plants to home
Today, some industries (automobile, electronics) are highly robotized, but home robots are still a thing of the future
But robots have rolled (are rolling) on Mars, fly autonomously, while others perform brain and heart surgery …
and humanoid robots are available for rent
Shahed University, Spring 2017 (

28. Natural Language Speech technologies (e.g. Siri)
Automatic speech recognition (ASR)
Text-to-speech synthesis (TTS)
Dialog systems
Language processing technologies
Question answering
Machine translation
Web search
Text classification, spam filtering, etc…

29. Vision (Perception) Object and face recognition Scene segmentation
Image classification
Demo1: VISION – lec_1_t2_video.flv
Images from Erik Sudderth (left), wikipedia (right)
Demo2: VISION – lec_1_obj_rec_0.mpg

30. Robotics Robotics Technologies In this class: Part mech. eng. Part AI
Demo 1: ROBOTICS – soccer.avi
Demo 4: ROBOTICS – laundry.avi
Demo 2: ROBOTICS – soccer2.avi
Demo 5: ROBOTICS – petman.avi
Demo 3: ROBOTICS – gcar.avi
Robotics
Part mech. eng.
Part AI
Reality much
harder than
simulations!
Technologies
Vehicles
Rescue
Soccer!
Lots of automation…
In this class:
We ignore mechanical aspects
Methods for planning
Methods for control
Images from UC Berkeley, Boston Dynamics, RoboCup, Google

31. Logic Logical systems Methods: Theorem provers NASA fault diagnosis
Question answering
Methods:
Deduction systems
Constraint satisfaction
Satisfiability solvers (huge advances!)
Image from Bart Selman

32. Game Playing Classic Moment: May, '97: Deep Blue vs. Kasparov
First match won against world champion
“Intelligent creative” play
200 million board positions per second
Humans understood 99.9 of Deep Blue's moves
Can do about the same now with a PC cluster
Open question:
How does human cognition deal with the
search space explosion of chess?
Or: how can humans compete with computers at all??
1996: Kasparov Beats Deep Blue
“I could feel --- I could smell --- a new kind of intelligence across the table.”
1997: Deep Blue Beats Kasparov
“Deep Blue hasn't proven anything.”
Huge game-playing advances recently, e.g. in Go!
Text from Bart Selman, image from IBM’s Deep Blue pages

33. Decision Making Applied AI involves many kinds of automation
Scheduling, e.g. airline routing, military
Route planning, e.g. Google maps
Medical diagnosis
Web search engines
Spam classifiers
Automated help desks
Fraud detection
Product recommendations
… Lots more!
All applications can be thought of as decision making or useful sub-components of decision making

34. Designing Rational Agents
An agent is an entity that perceives and acts.
A rational agent selects actions that maximize its (expected) utility.
Characteristics of the percepts, environment, and action space dictate techniques for selecting rational actions
This course is about:
General AI techniques for a variety of problem types
Learning to recognize when and how a new problem can be solved with an existing technique
Agent ?
Sensors
Actuators
Environment
Percepts
Actions

35. Pac-Man as an Agent Agent Environment Sensors ? Actuators
L1D2 =
python demos.py
Select Lecture 1  select demo 2
Percepts ?
Actions
Pac-Man is a registered trademark of Namco-Bandai Games, used here for educational purposes
Demo1: pacman-l1.mp4 or L1D2