SEG 4560 Final Review

Final

• 4:15-6:15pm, Friday April 24, 2009

• 6 Questions from Chapters 3-15a

• Two A4 size cheat sheets

• A calculator

• Useful materials: Tutorials 1-3, Assignments 1-3, Midterm, and Lecture notes

Chapter 15a

• Markov processes– Sensor model– Transition model

• Inference tasks– Filtering– Prediction– Smoothing– Most likely explanation

Chapter 14

• Bayesian networks– Network topology and CPTs– Express a full joint distribution with BN

• Inference tasks– Exact inference by enumeration– Exact inference by variable elimination– Approximate inference

Chapter 13

• Bayes’ Rule– Transform to a full joint distribution (or

probability with some hidden variables)– Sum over all hidden variables

• Independence and conditional independence

Chapters 7-9

• Express sentences in – Propositional logic– First-order logic

• Unification

• Entailment

Chapter 5

• CSPs– Variables– Domains– Constraints

• Backtracking search for CSPs

• Various heuristics to speedup search

Chapters 3-4• Uninformed search

– Breadth-first search– Uniform-cost search– Depth-first search– Depth-limited search– Iterative deepening search

• Informed search– Greedy search and A* search– Local search– Hill-climbing

• Properties of these search methods– Efficiency– Space– Completeness– Optimality