#VISUAL PROLOG 5.2 TUTORIAL GENERATOR#

Not only is this much easier to read, but if a goal that could fail was used in place of print, its failure would be correctly detected and passed on - whereas failures of the goals in a failure-driven loop are confused with the forced failure that drives the loop. The vast majority of Modern Prologs no longer require this syntax, instead providing a higher order predicate to address this. For example, to print all numbers up to a given limit: fdl(X) :- between(1,X,Y), print(Y), fail. Some 'classic' Prolog textbooks still use the confusing and error-prone failure-driven loop syntax where a fail construct is used to force backtracking to apply a goal to every value of a generator.

Visual Prolog does not include CLP(FD) in its standard library, although extension libraries for it are available. SWI-Prolog and other open Prologs often have some implementation. The acknowledged best development of CLP(FD) is in SICStus Prolog, which is commercial and expensive. Support for CLP(FD) is variable between Prologs. In this toy example, this does not increase performance because with such a small range as 1-10, the algebra processing takes as long as the loop would have done but when a larger range of numbers are being processed this may valuably reduce computation time.

Adding label() will cause X to loop only through the useful values 6.10. Using CLP(FD): ?- X in 1.10, Y #= X+5, Y #> 10.Р”В¬LP(FD) immediately does the maths and works out the available ranges. Prolog still loops through the values 1-5 even though it is mathematically provable from the given conditions that these values cannot be useful. For example, using old-style integer arithmetic: ?- trace. Using CLP can allow some intelligent reduction of brute force cases.

#VISUAL PROLOG 5.2 TUTORIAL GENERATOR#

The generator can be forced to run (and brute force constraints) using the label predicate: ?- X in 1.100, label(). Note that the generator does not actually run: only the range constraint is stored, ready for later constraints to be combined with it. Unlike is, #= is able to solve simple equations and unify in both directions: ?- 4 is 2+X.Р”В®RROR: is/2: Arguments are not sufficiently instantiatedР”В¬LP(FD) provides its own generator syntax. Once it is loaded, the #= syntax can take the place of both is and =:=.

CLP(FD) is based on storing the constraints that apply to an integer value and combining those together in memory.Р”В¬LP(FD) is an extension in most Prologs that support it, so must be loaded explicitly. However, several current Prologs offer CLP(FD) (Constraint Logic Programming over Finite Domains) as a cleaner alternative for integer arithmetic. Traditionally Prolog performed arithmetic using the is and =:= operators. This topic is intended to illustrate how modern Prolog has overcome some of the problems and rather crufty syntax that appears in older Prolog and may still be being introduced. Unfortunately, many Prolog textbooks and even teaching courses still introduce only the outdated prolog. Many modern Prolog systems are in continuous development and have added new features to address classic shortcomings of the language.

Visual prolog 5.2 tutorial