* means the notes are incomplete

• Syllabus
• What is AI?
  • The Turing test
  • A coffeehouse conversation
  • The knowledge level
• Search
  • Learning Python
  • Uninformed search
  • Informed search
  • Practice with searching
  • Adversarial search
• Knowledge representation
  • Boolean logic
  • Propositional logic
  • First order logic
  • Prolog
  • Prolog unification
  • Prolog resolution
  • Prolog examples
• Planning*
  • General Problem Solver (GPS)
  • Planning Domain Definition Language (PDDL)
• Multi-agent systems*
  • Ant intelligence*
  • NetLogo*
  • The prisoner's dilemma*
  • Particle swarm optimization*
• Machine Learning*
  • k-means clustering
  • Classification evaluation
  • k-nearest neighbor classification
  • Weka (machine learning software)
• Philosophical perspectives*
  • The "Chinese room" argument
  • The Norvig–Chomsky debate
  • Robot ethics*

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Material not covered in Spring 2014 but retained for reference.

• Search
  • Genetic algorithms
• Computer vision*
  • Image convolutions and transformations
  • Feature detection*
  • Object tracking*
  • Face detection*
• Machine Learning*
  • Bayesian inference
  • Naïve Bayesian classification
  • Text classification
  • Neural networks*

Intro to AI

• Homework 1 Due Fri 1/17, beginning of class
• Homework 2 Due Fri 1/24, beginning of class
• Homework 3 Due Wed 2/5, beginning of class
• Homework 4 Due Wed 2/19, beginning of class
• Homework 5 Due Fri 2/28, beginning of class
• Midterm Guide
• Homework 6 Due Sun 3/30, 11:59pm (in Dropbox)
• Homework 7 Due Wed 4/9, 11:59pm (in Dropbox)
• Homework 8 Due Fri 4/18, 11:59pm (in Dropbox)
• Final Guide Final: Wed 4/23, 10:00-11:45am, same room

• Videos of Spring 2014 lectures
• Videos of Autumn 2012 lectures

Intro to AI material by Joshua Eckroth is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License. Source code for this website available at GitHub.