Weekly outline

  • General

  • Week 1: Intro AI

    10/1: What is AI?
    10/3: Heuristic AI
    Readings: Textbook chs. 1-2

  • Week 2: Single-Agent Search

    10/8: Complete search
    10/10: Local search, CSPs
    Readings: Textbook chs. 3-4

  • Week 3: Applied Search

    10/15: Scheduling and planning
    10/17: Adversary search
    Readings: Textbook chs. 10.1-2, 11.1, 5

    • Week 4: Logic and AI

      10/22: Logical inference
      10/24: Logical knowledge representation
      Reading: Textbook chs. 9, 12 (and review chs. 7-8)

    • Week 5: Probability and Decision Theory

      10/29: Probability
      10/31: Decisions, optimization and Expert Systems
      Readings: Textbook chs. 13, 16

      • Week 6: Machine Learning

        11/05: Machine Learning methods
        11/07: Case study: Machine Learning
        Readings: Textbook ch. 18.1-18.6, 18.10-18.11

      • Week 7: Neural Nets and GAs

        11/12: Artificial Neural Nets
        11/14: Genetic Algorithms
        Reading: Textbook ch. 4.1.4, 18.7

        • Week 8: AI and Action

          11/19: Navigation, control, robotics
          11/21: Ensembles
          Reading: Textbook ch. 15, 18.1

        • Week 9: Ensembles

          11/26: Applications 1
          11/28: US Thanksgiving Holiday, no class meeting

          • Week 10: Applications

            12/3: Applications 2
            12/5: Concluding thoughts