Слайд 1Introduction to AI
Required textbook:
S. Russell and P. Norvig.
Artificial
Intelligence: A Modern Approach.
3rd edition, Prentice Hall, 2010
Слайд 2
AI is the reproduction of human reasoning and intelligent behavior
by computational methods
What is AI?
Слайд 3What is AI?
(R&N)
Discipline that systematizes and automates reasoning processes to
create machines that:
Слайд 4The goal of AI is to create computer systems that
perform tasks regarded as requiring intelligence when done by humans
AI 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 build a computer system that does it automatically
But do we want to duplicate human imperfections?
Слайд 5Here, how the computer performs tasks does matter
The reasoning steps
are important
Ability to create and manipulate symbolic knowledge (definitions,
concepts, theorems, …)
What is the impact of hardware on low-level reasoning, e.g., to go from signals to symbols?
Слайд 6Now, the goal is to build agents that always make
the “best” decision given what is available (knowledge, time, resources)
“Best”
means maximizing the expected value of a utility function
Connections to economics and control theory
What is the impact of self-consciousness, emotions, desires, love for music, fear of dying, etc ... on human intelligence?
Слайд 7Can Machines Act/Think Intelligently?
“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, …”
Discourse on the Method, by Descartes (1598-1650)
Слайд 8Turing Test:
http://plato.stanford.edu/entries/turing-test/
Test proposed by Alan Turing in 1950
The computer is
asked questions by a human interrogator. It passes the test
if the interrogator cannot tell whether the responses come from a person
Required capabilities: natural language processing, knowledge representation, automated reasoning, learning,...
No physical interaction
Chinese Room (J. Searle)
Can Machines Act/Think Intelligently?
Слайд 9An Application of the Turing Test
CAPTCHA: Completely Automatic Public Turing
tests to tell Computers and Humans Apart
E.g.:
Display visually distorted
words
Ask user to recognize these words
Example of application: have only humans open email accounts
Слайд 10Can Machines Act/Think Intelligently?
Yes, if intelligence is narrowly defined as
information processing
AI has made impressive achievements showing that tasks initially
assumed to require intelligence can be automated
But each success of AI seems to push further the limits of what we consider “intelligence”
Слайд 11Some Achievements
Computers have won over world champions in several games,
including Checkers, Othello, and Chess, but still do not do
well in Go
AI techniques are used in many systems: formal calculus, video games, route planning, logistics planning, pharmaceutical drug design, medical diagnosis, hardware and software trouble-shooting, speech
recognition, traffic monitoring,
facial recognition,
medical image analysis, part
inspection, etc...
Stanford’s robotic car, Stanley, autonomously traversed 132 miles
of desert
Some industries (automobile, electronics) are highly robotized,
while other robots perform brain
and heart surgery, are rolling
on Mars, fly autonomously, …,
but home robots still remain
a thing of the future
Слайд 12Can Machines Act/Think Intelligently?
Yes, if intelligence is narrowly defined as
information processing
AI has made impressive achievements showing that tasks initially
assumed to require intelligence can be automated
Maybe yes, maybe not, if intelligence is not separated from the rest of “being human”
Слайд 13Some Big Open Questions
AI (especially, the “rational agent” approach) assumes
that intelligent behaviors are only based on information processing? Is
this a valid assumption?
If yes, can the human brain machinery solve problems that are inherently intractable for computers?
In a human being, where is the interface between “intelligence” and the rest of “human nature”, e.g.:
How does intelligence relate to emotions felt?
What does it mean for a human to “feel” that he/she understands something?
Is this interface critical to intelligence? Can there exist a general theory of intelligence independent of human beings? What is the role of the human body?
Слайд 14Some Big Open Questions
AI (especially, the “rational agent” approach) assumes
that intelligent behaviors are based on information processing? Is this
a valid assumption?
If yes, can the human brain machinery solve problems that are inherently intractable for computers?
In a human being, where is the interface between “intelligence” and the rest of “human nature”, e.g.:
How does intelligence relate to emotions felt?
What does it mean for a human to “feel” that he/she understands something?
Is this interface critical to intelligence? Can there exist a general theory of intelligence independent of human beings? What is the role of the human body?
In the movie I, Robot, the most impressive feature of the robots is not their ability to solve complex problems, but how they blend human-like reasoning with other key aspects of human beings (especially, self-consciousness, fear of dying, distinction between right and wrong)
Слайд 15AI contributes to building an information processing model of human
beings, just as Biochemistry contributes to building a model of
human beings based on bio-molecular interactions
Both try to explain how a human being operates
Both also explore ways to avoid human imperfections (in Biochemistry, by engineering new proteins and drug molecules; in AI, by designing rational reasoning methods)
Both try to produce new useful technologies
Neither explains (yet?) the true meaning of being human
Слайд 16Main Areas of AI
Knowledge representation (including formal logic)
Search, especially heuristic
search (puzzles, games)
Planning
Reasoning under uncertainty, including probabilistic reasoning
Learning
Agent architectures
Robotics and
perception
Natural language processing
Search
Knowledge
rep.
Planning
Reasoning
Learning
Agent
Robotics
Perception
Natural
language
...
Expert
Systems
Constraint
satisfaction
Слайд 17Bits of History
1956: The name “Artificial Intelligence” is coined
60’s: Search
and games, formal logic and theorem proving
70’s: Robotics, perception,
knowledge representation, expert systems
80’s: More expert systems, AI becomes an industry
90’s: Rational agents, probabilistic reasoning, machine learning
00’s: Systems integrating many AI methods, machine learning, reasoning under uncertainty, robotics again
Слайд 18228
222
227
Reasoning
Methods in AI
Rational Agency
and Intelligent Interaction
224M
Multi-Agent
Systems
224N
Natural Language Processing
+ Speech
Recognition and Synthesis
224S
224U
227B
General
Game Playing
226
Statistical Techniques
in Robotics
229
Machine Learning
Structured
Probabilistic Models
157
Logic
& Automated
Reasoning