State-space search:

  state spaces; states, operators, and moves; 
  edge costs; shortest paths; 
  heuristic evaluation functions;
  recursive depth-first search;
  iterative depth-first search;
  breadth-first search;
  iterative-deepening depth-first search;
  uniform-cost search;
  best-first search; 
  A* search; 
  genetic search; 
  minimax search with alpha-beta pruning.

Predicate logic:

  predicates, terms, variables, constants,
  function symbols, quantifiers, well-formed formulas; 
  proof by perfect induction (truth tables);
  clause form; atomic formulas, literals, clauses,
  Horn clauses; substitutions, unifiers, most-general unifiers;
  Skolem constants;
  proofs by resolution in the predicate calculus.

Bayes rule.

Grammars: 

  terminal and non-terminal symbols, start symbol,
  productions, sentential forms, derivation, parsing;
  augmented transition networks.

Image understanding:

  sampling and quantization; thresholding;
  valley method for threshold selection;
  edge detection with Roberts cross operator;
  Hough transform for line detection,
  polar representation of a line;
  formal definition of segmentation into regions;
  Guzman labeling of line drawings of blocks-world scenes.

Asimov's three laws of robotics.