1 / 22

Declarative Loops and List Comprehensions for Prolog

Declarative Loops and List Comprehensions for Prolog. Neng-Fa Zhou Brooklyn College The City University of New York zhou@sci.brooklyn.cuny.edu. Motivation. Second ASP-solver Competition 38 problems were used The B-Prolog team was the only CLP(FD) team

ita
Download Presentation

Declarative Loops and List Comprehensions for Prolog

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Declarative Loops and List Comprehensions for Prolog Neng-Fa Zhou Brooklyn College The City University of New York zhou@sci.brooklyn.cuny.edu

  2. Motivation • Second ASP-solver Competition • 38 problems were used • The B-Prolog team was the only CLP(FD) team • We had to develop solutions from scratch • We desperately needed loop constructs

  3. One of the Problems:Maze generation • Conditions • 1. There must be a path from the entrance to every empty cell. • 2. There must be no 2x2 blocks of empty cells or walls. • 3. No wall can be completely surrounded by empty cells. • …

  4. The Array Subscript Notation for Structures and Lists in B-Prolog • In arithmetic expressions • In arithmetic constraints • In calls to @= and @:= • In any other context, X[I1,…,In] is the same as X^[I1,…,In] S is X[1]+X[2]+X[3] X[1]+X[2] #= X[3] X[1,2] @= 100X[1,2] @:= 100

  5. foreach(E1inD1, . . ., EninDn, Goal) • EiinDi • Ei is a pattern (usually a variable but can be a compound term) • Di is a collection (a list or a range of integers l..u) • Semantics • For each combination of values E1D1, . . ., EnDn, execute Goal

  6. Example-1 • Using foreach • Using recursion ?- L=[1,2,3],foreach(X in L, write(X)). ?- L=[1,2,3],write_list(L). write_list([]). write_list([X|T]) :- write(X), write_list(T).

  7. Example-2 • Using foreach • Using recursion ?- foreach(X in 1..3, write(X)). ?- write_int_range(1,3). write_int_range(I,N):-I>N,!. write_int_range(I,N) :- write(I), I1 is I+1, write_int_range(I1,N).

  8. Example-3 (compound patterns) • Using foreach • Using recursion (matching clauses) ?-L=[(a,1),(b,2)],foreach((A,I) in L, writeln(A=I)). ?- L=[(a,1),(b,2)],write_pairs(L). write_pairs([]) => true. write_pairs([(A,I)|L]) => writeln(A=I), write_pairs(L).

  9. foreach(E1inD1, . . ., EninDn, LVars, Goal) Variables in LVars are local to each iteration. • Using foreach • Using recursion ?-S=f(1,2,3), foreach(I in 1..S^lengh,[E], (E @= S[I], write(E))). ?-S=f(1,2,3),functor(S,_,N),write_args(S,1,N).write_args(S,I,N):-I>N,!.write_args(S,I,N):- arg(I,S,E), write(E), I1 is I+1, write_args(S,I1,N).

  10. List Comprehension [T : E1inD1, . . ., EninDn, LVars, Goal] • Calls to @=/2 • Arithmetic constraints ?- L @= [X : X in 1..5].L=[1,2,3,4,5]?-L @= [(A,I): A in [a,b], I in 1..2].L= [(a,1),(a,2),(b,1),(b,2)] sum([A[I,J] : I in 1..N, J in 1..N]) #= N*N

  11. foreach With Accumulators L @= [(A,I): A in [a,b], I in 1..2] foreach(A in [a,b], I in 1..2, ac1(L,[]), L^0=[(A,I)|L^1])

  12. Application Examples • Quick sort • Permutations • N-Queens • Non-boolean constraints • Boolean constraints • Gaussian elimination • No-Three-in-a-Line Problem • Maze generation

  13. Quick Sort qsort([],[]). qsort([H|T],S):- L1 @= [X : X in T, X<H], L2 @= [X : X in T, X>=H], qsort(L1,S1), qsort(L2,S2), append(S1,[H|S2],S).

  14. Permutations perms([],[[]]). perms([X|Xs],Ps):- perms(Xs,Ps1), Ps @= [P : P1 in Ps1, I in 0..Xs^length,[P], insert(X,I,P1,P)]. insert(X,0,L,[X|L]). insert(X,I,[Y|L1],[Y|L]):- I>0, I1 is I-1, insert(X,I1,L1,L).

  15. The N-Queens Problem Qi: the number of the row for the ith queen. queens(N):- length(Qs,N), Qs :: 1..N, foreach(I in 1..N-1, J in I+1..N, (Qs[I] #\= Qs[J], abs(Qs[I]-Qs[J]) #\= J-I)), labeling([ff],Qs), writeln(Qs).

  16. The N-Queens Problem (Boolean Constraints) Qij=1 iff the cell at (i,j) has a queen. bqueens(N):- new_array(Qs,[N,N]), Vars @= [Qs[I,J] : I in 1..N, J in 1..N], Vars :: 0..1, foreach(I in 1..N, sum([Qs[I,J] : J in 1..N]) #= 1), foreach(J in 1..N, sum([Qs[I,J] : I in 1..N]) #= 1), foreach(K in 1-N..N-1, sum([Qs[I,J] : I in 1..N, J in 1..N, I-J=:=K]) #=< 1), foreach(K in 2..2*N, sum([Qs[I,J] : I in 1..N, J in 1..N, I+J=:=K]) #=< 1), labeling(Vars).

  17. Gaussian Elimination

  18. Gaussian Elimination triangle_matrix(Matrix):-     foreach(I in 1..Matrix^length-1,           [Row,J],                                         (select_nonzero_row(I,I,Matrix,J)->               (I\==J-> (Row @= Matrix[I],                           Matrix[I] @:= Matrix[J],                    Matrix[J] @:= Row)                 ;                   true                ),            foreach(K in I+1..Matrix^length, trans_row(I,K,Matrix))           ;               true       ) ).

  19. No-Three-in-a-Line Problem no3_build(N):- new_array(Board,[N,N]), Vars @= [Board[I,J] : I in 1..N, J in 1..N], Vars :: 0..1, Sum #= sum(Vars), Sum #=< 2*N, foreach(X1 in 1..N, Y1 in 1..N, [L,SL], (L @= [Slope : X2 in 1..N, Y2 in 1..N, [Slope], (X2\==X1, Slope is (Y2-Y1)/(X2-X1))], sort(L,SL), % eliminate duplicates foreach(Slope in SL, sum([Board[X,Y] : X in 1..N, Y in 1..N, (X\==X1,Slope=:=(Y-Y1)/(X-X1))]) #< 3))), foreach(X in 1..N, sum([Board[X,Y] : Y in 1..N])#<3), labeling([Sum|Vars]), outputBoard(Board,Sum,N).

  20. Maze generation % There must be no 2x2 blocks of empty cells or walls foreach(I in 1..M-1, J in 1..N-1, (Maze[I,J]+Maze[I,J+1]+Maze[I+1,J]+Maze[I+1,J+1]#>0, Maze[I,J]+Maze[I,J+1]+Maze[I+1,J]+Maze[I+1,J+1]#<4)),

  21. Demo • B-Prolog version 7.4 • N-queens problem • www.probp.com/examples.htm

  22. Conclusion • Foreach and list comprehension constitute a better alternative for writing loops • Recursion • Failure-driven loops • Higher-order predicates (e.g., findall,maplist) • The do construct in ECLiPSe Prolog • Very useful when used on arrays • Significantly enhance the modeling power of CLP(FD)

More Related