This repository has been archived on 2023-08-20. You can view files and clone it, but cannot push or open issues or pull requests.
yap-6.3/packages/cplint/approx/bestfirst.pl

452 lines
16 KiB
Perl
Raw Normal View History

2010-03-18 15:11:21 +00:00
/*==============================================================================
* LPAD and CP-Logic reasoning suite
* File best.pl
* Goal oriented interpreter for LPADs based on SLDNF
* Copyright (c) 2009, Stefano Bragaglia
*============================================================================*/
:- dynamic rule/4, def_rule/2.
/* EXTERNAL FILE
* -------------
* The following libraries are required by the program to work fine.
*/
:- use_module(library(lists)).
:- use_module(library(system)).
:- use_module(library(ugraphs)).
:- use_module(params).
:- use_module(tptree_lpad).
2010-03-18 15:11:21 +00:00
:- use_module(utility).
% :- source.
% :- yap_flag(single_var_warnings, on).
/* SOLVING PREDICATES
* ------------------
* The predicates in this section solve any given problem with several class of
* algorithms.
*
* Note: the original predicates (no more need and eligible to be deleted) have
* been moved to the end of the file.
*/
/* solve(Goals, ProbLow, ProbUp, Count, ResTime, BddTime)
* ------------------------------------------------------
* This predicate computes the probability of a given list of goals using an
* iterative deepening, probability bounded algorithm.
* It also returns the number of handled BDDs and the CPUTime spent performing
* resolution and spent handling the BDDs.
*
* Note: when their derivation is cut, negative goals are added to the head of
* the goals' list to be solved during the following iteration.
*
* INPUT
* - GoalsList: given list of goal to work on. It can contains variables: the
* predicate returns in backtracking all the solutions and their equivalent
* lower and upper bound probability.
*
* OUTPUT
* - ProbLow: resulting lower bound probability for the given list of goals.
* - ProbUp: resulting upper bound probability for the given list of goals.
* - Count: number of BDDs generated by the algorithm.
* - ResTime: CPU time spent on performing resolution.
* - BddTime: CPU time spent on handling BDDs.
*/
solve(Goals, ProbLow, ProbUp, Count, ResTime, BddTime) :-
setting(k, K),
setting(min_error, MinError),
setting(prob_step, ProbStep),
ProbStepLog is log(ProbStep),
assert(low(0, 0.0)),
assert(up(1.0)),
init_ptree(1),
% NB: log(1.0) == 0.0 !!!
bestfirst([0.0-([], [], Goals)], 0, K, MinError, ProbStepLog, ProbLow, ProbUp, 0, Count, 0, ResTime, 0, BddTime),
delete_ptree(1),
retract(low(_, _)),
retract(up(_)).
/* bestfirst(GoalsList, Number, Amount, MinError, ProbStep,
* LowerProb1, UpperProb1, Count0, Count1, ResTime0, ResTime1, BddTime0, BddTime1)
* -----------------------------------------------------------------------------
* This recursive supporting predicate performs resolution for current iteration,
* handles equivalent BDDs (lower and upper one) and calls itself if the current
* probability error is still bigger than the given minimum error.
*
* INPUT
* - GoalsList: given list of goal to work on.
* - FoundList: given list of achieved solutions.
* - Amount: max number of solution considered by each iteration.
* - MinError: minimum error (closing condition).
* - ProbStep: probability step.
* - Count0: number of BDDs already handled by the algorithm.
* - ResTime0: cpu time already spent on performing resolution.
* - BddTime0: cpu time already spent on handling BDDs.
*
* OUTPUT
* - LowerProb1: resulting lower bound probability for the given list of goals.
* - UpperProb1: resulting upper bound probability for the given list of goals.
* - Count1: number of BDDs handled.
* - ResTime1: cpu time spent on performing resolution.
* - BddTime1: cpu time spent on handling BDDs.
*/
bestfirst(GoalsList, Number, Amount, MinError, ProbStep, LowerProb1, UpperProb1, Count0, Count1, ResTime0, ResTime1, BddTime0, BddTime1) :-
% Resetting the clocks...
statistics(walltime, [_, _]),
% Performing resolution...
main(GoalsList, Amount, ProbStep, List),
% Taking elapsed times...
statistics(walltime, [_, ElapResTime]),
ResTime2 is ResTime0 + ElapResTime/1000,
% Building and solving equivalent bdds...
init_ptree(2),
init_ptree(3),
separate(List, [], LowerList0, [], UpperList, [], Incomplete),
insert_list_ptree(LowerList0, 1),
insert_list_ptree(UpperList, 2),
merge_ptree(1,2,3),
length(LowerList0, DeltaLow),
Next is Number + DeltaLow,
eval_lower(Next, ProbLow),
length(UpperList, DeltaUp),
Temp is Next + DeltaUp,
eval_upper(Temp, ProbUp),
delete_ptree(2),
delete_ptree(3),
% Taking elapsed times...
Count2 is Count0 + 2,
statistics(walltime, [_, ElapBddTime]),
BddTime2 is BddTime0 + (ElapBddTime / 1000),
% Is the current error lower than the minimum error?
(ProbUp - ProbLow < MinError ->
% Setting output parameters' values...
LowerProb1 = ProbLow,
UpperProb1 = ProbUp,
Count1 = Count2,
ResTime1 = ResTime2,
BddTime1 = BddTime2;
% Keeping on iterating with accumulated values...
% sufficient without negation:
% D1 = DB,
% necessary for negation
bestfirst(Incomplete, Next, Amount, MinError, ProbStep, LowerProb1, UpperProb1, Count2, Count1, ResTime2, ResTime1, BddTime2, BddTime1)).
/* main(GoalsList, Amount, ProbStep, Pending)
* ------------------------------------------------
* This tail recursive predicate takes the given GoalsList and tries to solve
* the first given Amount quads with the given ProbStep bound on probability,
* one at a time. After each resolution step, it merges the new solutions to the
* current list of solutions so that each time it can consider the most
* promising solution. It finally returns the list of pending solutions, if any.
*
* INPUT
* - GoalsList: current list of goals to solve.
* - Amount: current number of goals to solve.
* - ProbStep: incremental probability step for bound.
*
* OUTPUT
* - Sorted: desired sorted (by non increasing prob) results.
*/
main([], _Amount, _Step, []) :- !.
%% Closing condition: stop if no more goals (pending list is an empty list).
main(Pending, Amount, _Step, Pending) :-
Amount =< 0, !.
%% Closing condition: stop if reached desired amount (pending list is current list).
main([Prob0-(Gnd0, Var0, Goals0)|Tail], Amount, Step, Pending) :-
%% Note: Current list is surely not empty.
%% Note: A certain amount is surely still needed.
Bound is Prob0 + Step,
findall(Prob1-(Gnd1, Var1, Goals1),
explore(Bound, Prob0-(Gnd0, Var0, Goals0), Prob1-(Gnd1, Var1, Goals1)),
List),
%% Find all the solutions reacheable from the first quad.
sort(List, Sorted),
merge(Tail, Sorted, Complete),
Needed is Amount - 1,
%% Count current quad as considered.
main(Complete, Needed, Step, Pending).
%% Recursive call: consider next quad (updating pending list).
%% Note: Complete list is sorted; this assures we always consider best quad.
/* merge(SortedA, SortedB, Sorted)
* -------------------------------
* This tail recursive predicate merges the quads in SortedA and SortedB list by
* non-increasing values of Prob and returns the desired unique Sorted list.
* The SortedA and SortedB lists must be sorted.
*
* INPUT
* - SortedA: first sorted list of quads.
* - SortedB: second sorted list of quads.
*
* OUTPUT
* - Sorted: resulting unique sorted list of quads.
*/
merge(Sorted, [], Sorted) :- !.
%% Closing condition: stop if no more items in first sorted list (current second sorted list is output sorted list).
merge([], Sorted, Sorted).
%% Closing condition: stop if no more items in first sorted list (current second sorted list is output sorted list).
merge([ProbA-(GndA, VarA, GoalsA)|TailA], [ProbB-(GndB, VarB, GoalsB)|TailB], [ProbA-(GndA, VarA, GoalsA)|Tail]) :-
ProbA >= ProbB, !,
merge(TailA, [ProbB-(GndB, VarB, GoalsB)|TailB], Tail).
%% Recursive call: use the first quad (merge the rest of the first list with the second one).
merge([ProbA-(GndA, VarA, GoalsA)|TailA], [ProbB-(GndB, VarB, GoalsB)|TailB], [ProbB-(GndB, VarB, GoalsB)|Tail]) :-
% ProbA < ProbB, !,
merge([ProbA-(GndA, VarA, GoalsA)|TailA], TailB, Tail).
%% Recursive call: use the second quad (merge the first list with the rest of the second one).
/* separate(List, Low, Up, Next)
* ----------------------------------
* This tail recursive predicate parses the input list and builds the list for
* the lower bound, the upper bound and the pending goals.
* The upper bound list contains both the items of the lower bound list and the
* incomplete ones.
*
* INPUT
* - List: input list.
*
* OUTPUT
* - Low: list for lower bound.
* - Up: list for upper bound.
* - Next: list of pending goals.
*/
separate(List, Low, Up, Next) :-
%% Polarization: initial low, up and next lists are empty.
separate(List, [], Low, [], Up, [], Next).
separate([], Low, Low, Up, Up, Next, Next) :- !.
%% Closing condition: stop if no more results (current lists are now final lists).
separate([_Prob-(Gnd0, [], [])|Tail], Low0, [Gnd0|Low1], Up0, [Gnd0|Up1], Next0, Next1) :- !,
separate(Tail, Low0, Low1, Up0, Up1, Next0, Next1).
separate([Prob0-(Gnd0, Var0, Goals)|Tail], Low0, Low1, Up0, [Gnd1|Up1], Next0, [Prob1-(Gnd1, Var1, Goals)|Next1]) :-
get_groundc(Var0, Gnd2, Var1, 1.0, Prob2),
append(Gnd0, Gnd2, Gnd1),
Prob1 is Prob0 + log(Prob2),
separate(Tail, Low0, Low1, Up0, Up1, Next0, Next1).
/* explore(ProbBound, Prob0-(Gnd0, Var0, Goals0), Prob1-(Gnd1, Var1, Goals1))
* --------------------------------------------------------------------------
* This tail recursive predicate reads current explanation and returns the
* explanation after the current iteration without dropping below the given
* probability bound.
*
* INPUT
* - ProbBound: the desired probability bound;
* - Prob0-(Gnd0, Var0, Goals0): current explanation
* - Gnd0: list of current ground choices,
* - Var0: list of current non-ground choices,
* - Prob0: probability of Gnd0,
* - Goals0: list of current goals.
*
* OUTPUT
* - Prob1-(Gnd1, Var1, Prob1, Goals1): explanation after current iteration
* - Gnd1: list of final ground choices,
* - Var1: list of final non-ground choices,
* - Prob1: probability of Gnd1,
* - Goals1: list of final goals.
*/
explore(_ProbBound, Prob-(Gnd, Var, []), Prob-(Gnd, Var, [])) :- !.
%% Closing condition: stop if no more goals (input values are output values).
explore(ProbBound, Prob-(Gnd, Var, Goals), Prob-(Gnd, Var, Goals)) :-
%% Closing condition: stop if bound has been reached (input values are output values).
Prob =< ProbBound, !.
% Negation, builtin
explore(ProbBound, Prob0-(Gnd0, Var0, [\+ Head|Tail]), Prob1-(Gnd1, Var1, Goals1)) :-
builtin(Head), !,
call((\+ Head)),
explore(ProbBound, Prob0-(Gnd0, Var0, Tail), Prob1-(Gnd1, Var1, Goals1)).
%% Recursive call: consider next goal (building next values)
% Negation
explore(ProbBound, Prob0-(Gnd0, Var0, [\+ Head|Tail]), Prob1-(Gnd1, Var1, Goals1)) :- !,
list2and(HeadList, Head), % ...
findall(Prob-(Gnd, Var, CurrentGoals), explore(ProbBound, 0.0-([], [], HeadList), Prob-(Gnd, Var, CurrentGoals)), List) ->
separate(List, [], LowerBound, [], _UpperBound, [], PendingGoals),
(PendingGoals \= [] ->
Var2 = Var0,
Gnd2 = Gnd0,
Goals1 = [\+ Head|Goals],
explore(ProbBound, Prob0-(Gnd2, Var2, Tail), Prob1-(Gnd1, Var1, Goals));
%% Recursive call: consider next goal (building next values)
choose_clausesc(Gnd0, Var0, LowerBound, Var),
get_groundc(Var, Gnd, Var2, 1, Prob),
append(Gnd0, Gnd, Gnd2),
Prob2 is Prob0 + log(Prob),
explore(ProbBound, Prob2-(Gnd2, Var2, Tail), Prob1-(Gnd1, Var1, Goals1))).
%% Recursive call: consider next goal (building next values)
% Main, builtin
explore(ProbBound, Prob0-(Gnd0, Var0, [Head|Tail]), Prob1-(Gnd1, Var1, Goals1)) :-
builtin(Head), !,
call(Head),
get_groundc(Var0, Gnd, Var2, 1, Prob),
append(Gnd0, Gnd, Gnd2),
Prob2 is Prob0 + log(Prob),
explore(ProbBound, Prob2-(Gnd2, Var2, Tail), Prob1-(Gnd1, Var1, Goals1)).
% Recursive call: consider next goal (building next values)
% Main, def_rule
explore(ProbBound, Prob0-(Gnd0, Var0, [Head|Tail]), Prob1-(Gnd1, Var1, Goals1)) :-
def_rule(Head, Goals0),
append(Goals0, Tail, Goals2),
get_groundc(Var0, Gnd, Var2, 1, Prob),
append(Gnd0, Gnd, Gnd2),
Prob2 is Prob0 + log(Prob),
explore(ProbBound, Prob2-(Gnd2, Var2, Goals2), Prob1-(Gnd1, Var1, Goals1)).
% Recursive call: consider next goal (building next values)
% Main, find_rulec
explore(ProbBound, Prob0-(Gnd0, Var0, [Head|Tail]), Prob1-(Gnd1, Var1, Goals1)) :-
find_rulec(Head, (R, S, N), Goals, Var0, _Prob),
explore_pres(ProbBound, R, S, N, Goals, Prob0-(Gnd0, Var0, Tail), Prob1-(Gnd1, Var1, Goals1)).
explore_pres(ProbBound, R, S, N, Goals, Prob0-(Gnd0, Var0, Goals0), Prob1-(Gnd1, Var1, Goals)) :-
(member_eq((N, R, S), Var0);
member_eq((N, R, S), Gnd0)), !,
append(Goals, Goals0, Goals2),
get_groundc(Var0, Gnd, Var2, 1, Prob),
append(Gnd0, Gnd, Gnd2),
Prob2 is Prob0 + log(Prob),
explore(ProbBound, Prob2-(Gnd2, Var2, Goals2), Prob1-(Gnd1, Var1, Goals)).
% Recursive call: consider next goal (building next values)
explore_pres(ProbBound, R, S, N, Goals, Prob0-(Gnd0, Var0, Goals0), Prob1-(Gnd1, Var1, Goals1)) :-
append(Var0, [(N, R, S)], Var),
append(Goals, Goals0, Goals2),
get_groundc(Var, Gnd, Var2, 1, Prob),
append(Gnd0, Gnd, Gnd2),
Prob2 is Prob0 + log(Prob),
explore(ProbBound, Prob2-(Gnd2, Var2, Goals2), Prob1-(Gnd1, Var1, Goals1)).
% Recursive call: consider next goal (building next values)
/* eval_lower(Number, Prob)
* ------------------------
* This predicate evaluates if there are proofs for the lower bound by
* running an external command (BDD resolution via files).
*/
eval_lower(Number, Prob) :-
low(Number, Prob).
eval_lower(Number, ProbLow) :-
Number > 0,
low(OldNumber, _),
Number \= OldNumber,
bdd_ptree_map(1, 'bddl.txt', 'bddl.par', 'bddl.map'),
run_file('bddl.txt', 'bddl.par', NewProbLow),
(NewProbLow = timeout ->
low(_, ProbLow);
ProbLow = NewProbLow,
retract(low(_, _)),
assert(low(Number, ProbLow))).
/* eval_upper(Number, Prob)
* ------------------------
* This predicate evaluates if there are proofs for the upper bound by
* running an external command (BDD resolution via files).
*/
eval_upper(0, ProbUp) :- !,
low(_, ProbUp).
eval_upper(_Number, ProbUp) :-
bdd_ptree_map(3, 'bddu.txt', 'bddu.par', 'bddu.map'),
run_file('bddu.txt', 'bddu.par', NewProbUp),
(NewProbUp = timeout->
up(ProbUp);
ProbUp = NewProbUp,
retract(up(_)),
assert(up(ProbUp))).
/* run_file(BDDFile, BDDParFile, Prob)
* -----------------------------------
* This predicate calls for the resolution of a BDD via file.
*/
run_file(BDDFile, BDDParFile, Prob) :-
ResultFile = 'result.txt',
library_directory(Dir),
setting(timeout, BDDTime),
(BDDTime = no ->
atomic_concat([Dir, '/LPADBDD -l ', BDDFile, ' -i ', BDDParFile,' > ', ResultFile], Command);
atomic_concat([Dir, '/LPADBDD -l ', BDDFile, ' -i ', BDDParFile,' -t ', BDDTime,' > ', ResultFile], Command)),
%statistics(walltime,_),
shell(Command, Return),
(Return =\= 0 ->
Status = timeout,
Prob = Status;
see(ResultFile),
read(elapsed_construction(_TimeConstruction)),
read(probability(Prob)),
read(elapsed_traversing(_TimeTraversing)),
seen,
%write(probability(Prob)),nl,
%read(_),
%delete_file(ResultFile),
Status = ok
% format("Construction time ~f traversing time ~f~Number",[TimeConstruction, TimeTraversing])
).
%statistics(walltime,[_,E3]),
%format(user,'~w ms BDD processing~Number',[E3]),
% format("Status ~a~Number",[Status]).
/* insert_list_ptree([Head|Tail], Trie)
* ------------------------------------
* This predicate inserts the given list in a trie.
*/
insert_list_ptree([], _Trie).
insert_list_ptree([Head|Tail], Trie) :-
reverse(Head, Head1),
insert_ptree(Head1, Trie),
insert_list_ptree(Tail, Trie).