Sep 11, 2006 ------------- - Recap - solving a CSP using constraint propagation - can just 'read off' the answer - solving a CSP using search - Recap 3 node graphs - example 1: maintaining arc consistency 'cleans' up the domains - example 2: after maintaining arc consistency, must still search - Arc consistency is really short-hand for - "2-consistency" - What is 3-consistency? - Fix values for two variables, there must be a legal value for the 3rd - Strong K-consistency is equivalent to - 1-consistency - 2-consistency - ... - (K-1)-consistency - K-consistency - In general to just 'read off' the answer - can try to maintain strong n-consistency for a graph with n nodes - Sometimes k width of the constraint graph - Computing the width of the constraint graph - first identify all orderings (top to bottom) of the graph - where constraints are from a node to some node before it - for each ordering - find the max degree of a node - find min degree across all max degrees - A different sounding approach is given in your book - but it is really the same thing - For Sudoku - can try to do strong-81 consistency - overkill - some intermediate level might be sufficient - Next topic: knowledge representation and reasoning - Representation and Reasoning - given KB (facts) - try to derive conclusions (more facts) - General theme - setup an interpretation - setup an inference procedure - Logics - many kinds - mostly we will study monotonic logic - propositional logic - predicate logic - Non-monotonic logic - "Tweety is a canary." - "A canary is a bird." - "Birds fly." - can infer "Tweety flies." - but, if we add - "Tweety's wings are broken." - need to retract earlier conclusion - cannot do this in propositional (or predicate) logic - Propositional logic - propositions: p, q, r - AND, OR, NOT - p=>q is the same as (NOT p OR q) - p<=>q is the same as (p=>q AND q=>p) - Which of these operators are really important? - can we remove some so that others can be derived from it? - yes! (which ones?)