Final review

Foundations of AI

• Definitions of AI
• Turing Test

Methods in AI

• State-Space Search

  • Problem Domains

    • Satisfaction
    • Optimization
    • Pathfinding
    • Etc

  • Methods

    • Local Search

    • Complete Search

      • DFS and Iterative Deepening
      • BFS, Dijkstra, A*

    • Logical Representation, SAT solvers

    • Adversary Search

• Statistical and ML

  • Types of ML

    • Unsupervised
    • Supervised
    • Reinforcement

  • Methods

    • K-Nearest Neighbor
    • Bayesian and Naive Bayesian
    • Information Gain and Decision Trees
    • Perceptrons and Neural Nets

• Other Emergent Systems

  • GAs
  • Ant Colony etc
  • Particle Filters

• Applications

  • Direct stuff: puzzle-solving, gameplay, routefinding
  • Robotics etc: Navigation and control

Ethics of AI