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Date: Mon, 02 Dec 1996 16:01:01 GMTServer: NCSA/1.4.2Content-type: text/html <html><TITLE>CSE 473 TOPICS FOR FINAL EXAM</TITLE><body><H1>CSE 473 Topic List for the Final Exam<br></h1> <p><H2>Common Lisp: Evaluation of S-expressions involving</H2><ol><li> CONS, LIST, APPEND, LET, FIRST, REST, +, *, NULL, =,<li> SETF, APPLY, QUOTE, DEFUN, IF, PROGN, LAMBDA</ol><H2>Production systems and pattern matching</H2><ol><li> Unordered and ordered production systems<li> Discrimination nets</ol><H2>Knowledge representation</H2><ol><li> ISA Hierarchies and Partial Orders<li> Propositional Calculus Truth tables, rules of inference<li> Predicate Calculus<li> Well-formed formulas<li> Semantics: Interpretations and models<li> Quantification and representation of unique existence</ol><H2>State-space search</H2><ol><li> Computing the size of the state space for the painted squares puzzle<li> Iterative formulation of depth-first search<li> Breadth-first search, best-first search, uniform-cost search<li> A* search algorithm, with f'(n) = g'(n) + h'(n)<li> Genetic search</ol><H2>Logical reasoning</H2><ol><li> Proofs in the propositional calculus by perfect induction<li> Resolution in the propositional calculus<li> Satisfiability, Tautology and Contradiction in the propositional calculus<li> Predicate calculus literals and clauses<li> Reduction to clause form<li> Unification, most general unifiers<li> Predicate calculus resolution<li> Satisfiability, tautology and contradiction in the predicate calculus</ol><H2>Probabilistic reasoning</H2><ol><li> Bayes rule<li> Odds</ol><H2>Commonsense reasoning</H2><ol><li> Case-based reasoning approach to problem solving<li> Distance functions and distance metrics</ol><H2>Planning</H2><ol><li> Difference between world space and plan space<li> Iterative-deepening depth-first search</ol><H2>Learning</H2><ol><li> Learning as improvement as measured by a function of merit, etc.<li> Concept synthesis in theory formation, example of prime numbers in AM</ol><H2>Natural-language understanding</H2><ol><li> Levels of NLU from acoustic to pragmatic<li> Semantic grammar</ol><H2>Vision</H2><ol><li> Edge detection with the Roberts cross operator<li> Representing contours with chain codes<li> Hough transform (how it works and its main formula)<li> Medial axis transform ("skeleton")<li> Ramer's algorithm for polygonal approximation<li> Guzman's method for labelling a line drawing of blocks</ol><H2>Neural networks</H2><ol><li> Perceptrons<li> Fundamental training theorem for perceptrons</ol><p><HR><address>tanimoto@cs.washington.edu</address></html>⌨️ 快捷键说明
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