Course Outline

AI: A Modern Approach, Russell & Norvig, 1994.

Supplemental material when I can find it.

• Constraint Satisfaction
  • systematic search, stochastic search
• Combinatorial Optimization
  • simulated annealing
• Function Approximation
  • polynomial regression, neural networks, decision trees
• Probabilistic Inference
  • belief networks, statistical natural language processing, hidden Markov models
• Control
  • Markov decision processes, planning, reinforcement learning

My hope is to present a set of general algorithmic tools that you can use in whatever applications you encounter in your work.