AI2 Module 1: hints for exam revision
The examinable material is everything presented in the lectures, the tutorials
and in the assignment. The suggestions for background reading go well beyond
what is examinable, though you may find background reading useful if you
have difficulty understanding any of the primary material.
Here are things that the exam may ask you to do:
- Show how one of the algorithms presented in the module handles a small
example (example algorithms: calculating utility of states in a static
environment, means ends analysis, the Viterbi algorithm, AC-3, using
truth tables, proving a theorem in the propositional calculus with
provided rules of inference, stochastic hillclimbing, GSAT). E.g. as in
the tutorial exercises.
- Produce short definitions of key terms (e.g. "constraint", "planning
island", "HMM", "arc consistency", "edge labelling", "memoisation",
"search strategy", "entailment", "refutation", "clause", "SAT",
"simulated annealing").
- Use notations like the graphical notation for CSPs,
propositional logic, the graphical notation for search spaces, to
represent simple problems/possible solutions.
- Show that you understand the differences between different algorithms for
solving a problem, e.g. a naive Prolog approach vs the "backtracking"
approach to constraint satisfaction, the Prolog vs the CLP approach to
arithmetic, depth first search vs iterative deepening, theorem proving
vs truth tables, David-Putnam vs GSAT.
Back to the AI2 Module 1 home page
This page is maintained by the course lecturer, Bob Fisher,
r.b.fisher@ed.ac.uk, room 2107D JCMB, Tel 651-3441
