AI Chapter 1: Introduction to Artificial Intelligence

Introduction to Artificial Intelligence

• This course provides an introduction to Artificial Intelligence techniques
• Covers problem solving, knowledge representation and reasoning, and uncertain knowledge representation and reasoning

Course Outline

• What is AI?
• The Foundations of AI
• The History of AI
• Fundamental Techniques of AI
• AI in Everyday Life
• Some Sub-fields of AI

Rise of AI

• In March 2016, AlphaGo defeated Lee Sedol, a South Korean 9-dan professional Go player, by 4-1
• Birth of AI: Dartmouth Workshop in August 1956, where scientists and mathematicians discussed how to make machines simulate human learning and other features of intelligence

What is Intelligence?

• Defined as the capacity to acquire and apply knowledge and the ability of thought and reason

What is AI?

• Charniak and McDermott: “Artificial intelligence is the study of mental faculties through the use of computational models.”
• Shapiro: “Artificial intelligence is a field of science and engineering concerned with the computational understanding of what is commonly called intelligent behavior, and with the creation of artifacts that exhibit such behavior.”
• Rich and Knight: “The study of how to make computers do things at which, at the moment, people are better.”
• Russell and Norvig: four categories of AI definitions:
  • Human Performance
  • Ideal Performance
  • Thinking Humanly
  • Acting Rationally

Acting Humanly: The Turing Test Approach

• Designed to provide a satisfactory operational definition of intelligence
• A computer passes the test if a human interrogator cannot tell whether written responses come from a person or a computer
• Suggested major components of AI:
  • Natural Language Processing
  • Knowledge Representation
  • Automated Reasoning
  • Machine Learning
  • Computer Vision
  • Robotics

Thinking Humanly: The Cognitive Modeling Approach

• Determining how humans think through introspection, psychological experiments, and brain imaging
• Cognitive science brings together computer models from AI and experimental techniques from psychology to construct precise and testable theories of the human mind

Thinking Rationally: Laws of Thought

• Normative (or prescriptive) rather than descriptive
• Aristotle: what are correct arguments/thought processes?
• Several Greek schools developed various forms of logic

Acting Rationally

• Rational behavior: doing the right thing, which is expected to maximize goal achievement, given the available information
• An agent is an entity that perceives and acts
• An intelligent agent: its actions are appropriate for its goals and circumstances, is flexible to changing environments and goals, learns from experience, and makes appropriate choices given perceptual limitations and limited resources

The Foundations of AI

• Artificial intelligence is a science and technology based on multiple disciplines, including computer science, linguistics, biology, mathematics, psychology, and engineering

The History of AI

• 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, and Gelernter's Geometry Engine
• 1956: Dartmouth meeting: “Artificial Intelligence” adopted
• 1965: Robinson's complete algorithm for logical reasoning
• 1966-74: AI discovers computational complexity - Neural network research almost disappears
• 1969-79: Early development of knowledge-based systems
• 1980-88: Expert systems industry booms
• 1988-93: Expert systems industry busts: “AI Winter”
• 1985-95: Neural networks return to popularity
• 1988-: Resurgence of probability; general increase in technical depth - “Nouvelle AI”: ALife, GAs, soft computing
• 1995-: Agents, agents, everywhere
• 2003-: Human-level AI back on the agenda

Introduction to AI

• The course provides an introduction to Artificial Intelligence techniques
• Topics covered include:
  • Introduction to AI
  • Problem Solving
  • Knowledge Representation and Reasoning
  • Uncertain Knowledge Representation and Reasoning

Course Textbook

• Russell, S. and Norvig, P. Artificial Intelligence: A Modern Approach. Prentice Hall, 4th edition, 2018
• Luger, F., George. Artificial Intelligence: Structures and Strategies for Complex Problem Solving. Addison-Wesley, 6th edition, 2009

What is AI?

• Intelligence may be defined as:
  • The capacity to acquire and apply knowledge
  • The ability of thought and reason
• Definitions of AI:
  • Charniak and McDermott: "Artificial intelligence is the study of mental faculties through the use of computational models"
  • Shapiro: "Artificial intelligence is a field of science and engineering concerned with the computational understanding of what is commonly called intelligent behavior, and with the creation of artifacts that exhibit such behavior"
  • Rich and Knight: "The study of how to make computers do things at which, at the moment, people are better"

Categories of AI Definitions

• According to Russell and Norvig, definitions of AI fall into four categories:
  • Human Performance
  • Ideal Performance
  • Thinking Humanly
  • Thinking Rationally

Turing Test Approach

• The Turing Test, proposed by Alan Turing (1950), was designed to provide a satisfactory operational definition of intelligence
• A computer passes the test if a human interrogator, after posing some written questions, cannot tell whether the written responses come from a person or from a computer
• Major components of AI:
  • Natural Language Processing
  • Knowledge Representation
  • Automated Reasoning
  • Machine Learning
  • Computer Vision
  • Robotics