Midterm Test Review Topics

 

Chapter 1:

  1. AI definitions and Turing test
  2. AI application areas

 

Chapter 2:

  1. Predicate/Proposition logic
  2. Deductive Inference – modus ponens
  3. Unification and most general unifier: definition and process

 

Chapter 3:

  1. State space and search
  2. Data-driven and goal-driven search and implementation
  3. Backtrack
  4. Depth-first and breadth-first search and implementation
  5. State space representation of predicate/propositional calculus
  6. And/or graphs

 

Chapter 4:

  1. Hill-climbing search
  2. Best-first search and implementation
  3. Heuristics search
  4. Heuristic functions
  5. A and A* algorithms
  6. Admissibility, monotonicity, and informedness
  7. Minimax procedure
  8. Alpha-beta procedure

 

Chapter 5:

  1. Probability, prior and post (conditional) probability
  2. Bayes’ theorem

 

Chapter 6:

  1. Recursion-based search
  2. Pattern-driven reasoning
  3. Production systems: architecture, components, pros and cons
  4. Search control in production systems: data-driven, goal-driven, rule structure, conflict resolution
  5. Advantages of production systems