Artificial Intelligence
INTRODUCTION: CHAPTER 1
Textbook: S. Russell and P. Norvig Artificial Intelligence: A Modern
Approach Prentice Hall,
Outline
Course overview
What is AI?
A brief history
The state of the art
What is AI?
Views of AI fall into four categories (System):
Acting Humanly Acting rationally
Thinking Humanly Thinking Rationally
The textbook advocates "acting rationally"
Thinking / Acting | Humanly/Rationally
Thinking humanly — cognitive modeling. Systems
should solve problems the same way humans do.
Thinking rationally — the use of logic. Need to worry
about modeling uncertainty and dealing with
complexity.
Acting humanly — the Turing Test approach.
Acting rationally — the study of rational agents:
agents that maximize the expected value of their
performance measure given what they currently
know.
Some Definitions
The study of agents that receive percepts from the environment and perform
actions. (Russell and Norvig)
The science and engineering of making intelligent machines, especially intelligent
computer programs (John McCarthy)
The ability of a digital computer or computer-controlled robot to perform tasks
commonly associated with intelligent beings (Encyclopædia Britannica)
The study of ideas to bring into being machines that respond to stimulation
consistent with traditional responses from humans, given the human capacity for
contemplation, judgment and intention (Latanya Sweeney)
The scientific understanding of the mechanisms underlying thought and intelligent
behavior and their embodiment in machines (American Association for Artificial
Intelligence)
A branch of science which deals with helping machines find solutions to complex
problems in a more human-like fashion (AI depot)
A field of computer science that seeks to understand and implement computer-
based technology that can simulate characteristics of human intelligence and human
sensory capabilities (Raoul Smith)
Acting humanly: Turing Test
Turing (1950) "Computing machinery and intelligence":
"Can machines think?" "Can machines behave intelligently?"
Operational test for intelligent behavior: the Imitation Game
Predicted that by 2000, a machine might have a 30% chance of fooling
a lay person for 5 minutes
Anticipated all major arguments against AI in following 50 years
Suggested major components of AI: knowledge, reasoning, language
understanding, learning
Thinking humanly: cognitive modeling
1960s "cognitive revolution": information-processing
psychology
Requires scientific theories of internal activities of the brain
-- How to validate? Requires
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
Thinking rationally: "laws of thought"
Aristotle: what are correct arguments/thought processes?
Several Greek schools developed various forms of logic:
notation and rules of derivation for thoughts; may or may not
have proceeded to the idea of mechanization
Direct line through mathematics and philosophy to modern AI
Problems:
1. Not all intelligent behavior is mediated by logical deliberation
2. What is the purpose of thinking? What thoughts should I have?
3.
Acting rationally: rational agent
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
Rational agents
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
Caveat: computational limitations make perfect rationality
unachievable
design best program for given machine resources
AI prehistory
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
Abridged history of AI
1943 McCulloch & Pitts: Boolean circuit model of brain
1950 Turing's "Computing Machinery and Intelligence"
1956 Dartmouth meeting: "Artificial Intelligence" adopted
1952—69 Look, Ma, no hands!
1950s Early AI programs, including Samuel's checkers
program, Newell & Simon's Logic Theorist,
Gelernter's Geometry Engine
1965 Robinson's complete algorithm for logical reasoning
1966—73 AI discovers computational complexity
Neural network research almost disappears
1969—79 Early development of knowledge-based systems
1980-- AI becomes an industry
1986-- Neural networks return to popularity
1987-- AI becomes a science
1995-- The emergence of intelligent agents
State of the art
Deep Blue defeated the reigning world chess champion
Garry Kasparov in 1997
Proved a mathematical conjecture (Robbins conjecture)
unsolved for decades
No hands across America (driving autonomously 98% of
the time from Pittsburgh to San Diego)
During the 1991 Gulf War, US forces deployed an AI
logistics planning and scheduling program that involved up
to 50,000 vehicles, cargo, and people
NASA's on-board autonomous planning program
controlled the scheduling of operations for a spacecraft
Proverb solves crossword puzzles better than most
humans
