(note that the schedule and topics may change)

• Week 0 (Sept 27)
  • topics: general introduction to AI
  • reading: Chapter 1 in the text
  • slides: introduction to AI
  • background reading:
    • Stanley, the robot that won the DARPA Grand Challenge, S. Thrun et al, Journal of Robotics, 2006.
      • information about the DARPA Grand Challenge, including the 2007 Challenge competition (happening Nov 3rd)
      • The official DARPA Grand Challenge Web site
    • Learning and Multiagent Reasoning for Autonomous Agents, P. Stone, lecture slides from the IJCAI 2007 Computers and Thought Lecture, International Joint Conference on AI 2007. (also, video of the lecture)
      
      
• Week 1 (Oct 2nd)
  • topics: agents, problem solving, state-spaces, uninformed search
  • reading: Chapters 2 and 3 in the text
  • slides:
    • problem-solving using state-space search
    • uninformed search algorithms

• Week 2 (Oct 9th)
  • topics: informed search methods: A*, heuristic functions, local search methods
  • reading: Chapter 4 in the text
  • slides:
    • informed/heuristic search
    • local search and optimization
  • background reading:
    • Real-Time Adaptive A*. S. Koenig and M. Likhachev, 2006. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS)
  
  
• Week 3 (Oct 16th)
  • topics: constraint satisfaction problems: backtracking methods, local search
  • reading: Chapter 5 in the text
  • slides:
    • constraint satisfaction problems
  • background reading:
    • An experimental study of the coloring problem on human subject networks, Kearns, Suri, Montfort, Science 2006
    • Exploiting the deep structure of hard problems, Hogg and Williams, AI Journal, 1994
      
      
• Week 4 (Oct 23rd)
  • topics: games and adversarial search: minimax, alpha-beta pruning, evaluation functions, games with chance
  • reading: Chapter 6 in the text
  • slides:
    • adversarial search and game-playing
  
  
• Week 5 (Oct 30th)
  • topics: introduction to propositional logic
  • reading: Chapter 7 in the text
  • slides: propositional logic
  • This Saturday (Nov 3rd) the 2007 DARPA grand challenge takes place in Victorville, CA

• Week 6 (Nov 6)
  • topics: inference in propositional logic
  • reading: Chapter 7
  • Thursday: in-class MIDTERM EXAM, closed-book, closed-notes
    
    
• Week 7 (Nov 13)
  • topics: first-order logic, representation and inference
  • reading: Chapters 8 and 9 in the text
  • slides:
    • first-order logic
    • inference for first-order logic
  • background reading:
    • An introduction to the Syntax and Content of Cyc, Matuszek et al, AAAI Spring Symposium, 2006
    • Searching for commonsense: populating Cyc from the Web , Matuszek et al, AAAI 2005
      
      
• Week 8 (Nov 20)
  • topics: introduction to uncertainty, Bayesian networks
  • reading: Chapter 13 and 14.1 and 14.2 in the text
  • slides: knowledge and uncertainty
  • No lecture Thursday (Thanksgving holiday)
    
    
• Week 9 (Nov 27)
  • topics: inference in Bayesian networks; introduction to machine learning
  • reading:
  • slides:
    • Bayesian networks
    • Introduction to machine learning

• Week 10 (Dec 4)
  • topics: decision tree learning; perceptrons; boosting
  • slides:
    • Machine learning: part 2
  • background reading:
    • A short introduction to boosting, Y. Freund and R. Schapire, 1999
    • Robust real-time face detection, P. Viola and M. Jones, 2004
      
      
• Finals Week (Dec 11)
  • Final exam: Thursday Dec 13th, 1:30 to 3:30
  • Exam format: closed book, closed notes