Introduction to Artificial Intelligence http://www-courses.cs.uiuc.edu/~cs440/. Tuesday and Thursdays 2:00 to 3:15pm, 1404 Siebel Center Jean Ponce firstname.lastname@example.org 2065 Beckman Institute 333-8864. TA. Tuna Oezer (email@example.com) 1121 Siebel
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Tuesday and Thursdays
2:00 to 3:15pm, 1404 Siebel Center
2065 Beckman Institute
Office hours: Mon. 2:00-3:00 and Th. 1:00-2:00.
Knowing a lot?
Being able to pass as a smart human?
Being able to reason?
Being able to learn?
Being able to perceive and act upon one’s environment?
Passing an AI class?What is AI?
“AI is the study of ideas that enable computers to be intelligent.” [P. Winston]
So, what is intelligence?
`”The automation of activities that we associate with human thinking, activities such as decision-making, problem solving, learning…”
“The study of mental faculties through the use of computational models.”
[Charniak & McDermott, 1985]Operational Definitions of AI?
”The study of how to make computers do things at which, at the moment, people are better.”
[Rich& Knight, 1991]
“The branch of computer science that is concerned with the automation of intelligent behavior.”
Which do we choose?
Turing (1950) ``Computing machinery and intelligence'':
Notation and rules of derivation for thoughts.
The meaning of words and sentences
1943 McCulloch & Pitts: Boolean circuit model of brain
1950 Turing's ``Computing Machinery and Intelligence''
1950s Early AI programs, including Samuel's checkers program,
Newell & Simon's Logic Theorist, Gelernter's Geometry Engine
1956 McCarthy organizes Dartmouth meeting and includes Minsky,
Shannon, Newell, Samuel, Simon
Name ``Artificial Intelligence'' adopted
1958 Creation of the MIT AI Lab by Minsky and McCarthy
1963 Creation of the Stanford AI Lab by McCarthy
1965 Robinson's complete algorithm for logical reasoning
1966-74 AI discovers computational complexity …
1966-72 Shakey, SRI’s Mobile Robot [Fikes, Nilson]
1969 Publication of “Perceptrons” [Minsky & Papert],
Neural network research almost disappears
1969-79 Early development of knowledge-based systems
1971 MACSYMA, an symbolic algebraic manipulation system
1980-88 Expert systems industry booms
US: Microelectronics and Computer Technology Corp.
1988-93 Expert systems industry busts: ``AI Winter''
1985-95 Neural networks return to popularity
1988- Resurgence of probabilistic and decision-theoretic methods
Computational learning theory
``Nouvelle AI'': ALife, GAs, soft computing
Stuart Russell and Peter Norvig, “Artificial Intelligence: A Modern Approach” (2nd edition), Prentice-Hall, 2003.
Introduction (Ch. 1)
Problem solving and search (Ch. 3)
Informed search methods (Ch. 4)
Logical agents (Ch. 7)
First-order logic and inference (Ch. 8 and 9)
Resolution and planning (Ch. 9 and 11)
Uncertainty (Ch. 13)
Bayesian networks (Ch. 14)
Learning (Ch. 18 and 19)
Neural networks (Ch. 20)
Vision and robotics (Ch. 24 and 25)
Anagent is an entity that perceives and acts.
Abstractly, an agent is a function from percept histories to actions:
For any given class of environments and tasks, we seek the agent (or class of agents) with the best performance.
What is it all for?