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CSE 571 Advanced Artificial Intelligence

CSE 571 Advanced Artificial Intelligence. Oct 22, 2003 Class Notes Transcribed By: Jon Lammers. Ch8 – Smodels, DLV, Pure Prolog. Smodels & DLV Compute answer sets and compare to results. Pure Prolog Looks for items in result in the head. Works if you don’t use cut or ordering.

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CSE 571 Advanced Artificial Intelligence

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  1. CSE 571Advanced Artificial Intelligence Oct 22, 2003 Class Notes Transcribed By: Jon Lammers

  2. Ch8 – Smodels, DLV, Pure Prolog • Smodels & DLV • Compute answer sets and compare to results. • Pure Prolog • Looks for items in result in the head. • Works if you don’t use cut or ordering. • 8.4 discusses when Prolog is faithful to the entail relationship. • Prolog may be better for AnsProlog in cases where the answer sets are not computable (i.e. lists, ask a question). CSE 571 - Advanced Artificial Intelligence

  3. Graph Colorability (8.1.5) • Can you color a graph so that no adjacent vertices have the same color? vertex(1..4). edge(1,2). edge(1,3). edge(1,4). edge(2,3). Edge(2,4). 1{color(1,Y):col(Y)}1. % To start with. generalize to: 1{color(1,Y):col(Y)}1 :- vertex(X). :- color(X,Y), color(Z,Y), edge(X,Z). CSE 571 - Advanced Artificial Intelligence

  4. Knapsack Problem (8.1.8) • Items with size and value. Optimize the value of items that fit in a limited size sack. CSE 571 - Advanced Artificial Intelligence

  5. Knapsack Problem (8.1.8) • Weight • similar to 1 { a, b, c } 2 • Use 4 [ a, b, c ] 8. • Where weight a = 3, b = 5, c = 7. weight value(1) = 5. weight cost(1) = 4. weight value(2) = 6. weight cost(1) = 5. weight value(3) = 3. weight cost(1) = 6. weight value(4) = 8. weight cost(1) = 5. weight value(5) = 2. weight cost(1) = 3. %Limit to the size of the bag (cost). :- 13[ cost(X) : item( X ) ]. CSE 571 - Advanced Artificial Intelligence

  6. Knapsack Problem (8.1.8) inbag(X) :- item(X), not n_inbag(X). % iterate items n_inbag(X) :- item(X), not inbag(X). 1 { inbag(X), n_inbag(X) } 1 :- item(X). % iterate cost(X) :- inbag(X), item(X). val(X) :- inbag(X), item(X). maximize [ val(X) : item(X) ]. % Find max value. CSE 571 - Advanced Artificial Intelligence

  7. Single Unit Auction (8.1.9) • Auctioneer putting bundle of items up for auction. • Bidders bid on one or more items. • Auctioneer wishes to maximize his revenue from the auction. • Read this example and finish 8.1, 8.2, 8.3 CSE 571 - Advanced Artificial Intelligence

  8. Pure Prolog (8.3.1) • Smodels doesn’t support general lists. • It cannot build arbitrarily large structures. • Can only build finite length. • Can check lists. • Is p(1..5) defined for all in set S? p(1..5). in(1, S). in(2, S). in(3, S). in(4, S). in(5, S). not_true :- in(X, S), not p(X). true :- not not_true. CSE 571 - Advanced Artificial Intelligence

  9. Pure Prolog Weight_sold(X,Y,Z) = Y. Total_sold(I,N) :- item(I), number(N), N[sold(I,X,D) : number(X) : date(D)]N. • This is an inefficient implementation if N is grounded from 1 to 100. CSE 571 - Advanced Artificial Intelligence

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