c78a210afc
git-svn-id: https://yap.svn.sf.net/svnroot/yap/trunk@1864 b08c6af1-5177-4d33-ba66-4b1c6b8b522a
181 lines
6.6 KiB
TeX
181 lines
6.6 KiB
TeX
@chapter Constraint Logic Programming over Reals
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YAP now uses the CLP(R) package developed by @emph{Leslie De Koninck},
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K.U. Leuven as part of a thesis with supervisor Bart Demoen and daily
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advisor Tom Schrijvers, and distributed with SWI-Prolog.
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This CLP(R) system is a port of the CLP(Q,R) system of Sicstus Prolog
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and YAP by Christian Holzbaur: Holzbaur C.: OFAI clp(q,r) Manual,
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Edition 1.3.3, Austrian Research Institute for Artificial
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Intelligence, Vienna, TR-95-09, 1995,
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@url{http://www.ai.univie.ac.at/cgi-bin/tr-online?number+95-09} This
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port only contains the part concerning real arithmetics. This manual
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is roughly based on the manual of the above mentioned @strong{CLP(QR)}
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implementation.
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Please note that the @file{clpr} library is @emph{not} an
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@code{autoload} library and therefore this library must be loaded
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explicitely before using it:
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@example
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:- use_module(library(clpr)).
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@end example
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@node CLPR Solver Predicates, CLPR Syntax , , CLPR
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@section Solver Predicates
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@c =============================
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The following predicates are provided to work with constraints:
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@table @code
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@item @{+@var{Constraints}@}
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Adds the constraints given by @var{Constraints} to the constraint store.
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@item entailed(+@var{Constraint})
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Succeeds if @var{Constraint} is necessarily true within the current
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constraint store. This means that adding the negation of the constraint
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to the store results in failure.
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@item inf(+@var{Expression},-@var{Inf})
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Computes the infimum of @var{Expression} within the current state of the
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constraint store and returns that infimum in @var{Inf}. This predicate
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does not change the constraint store.
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@item inf(+@var{Expression},-@var{Sup})
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Computes the supremum of @var{Expression} within the current state of
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the constraint store and returns that supremum in @var{Sup}. This
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predicate does not change the constraint store.
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@item min(+@var{Expression})
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Minimizes @var{Expression} within the current constraint store. This is
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the same as computing the infimum and equation the expression to that
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infimum.
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@item max(+@var{Expression})
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Maximizes @var{Expression} within the current constraint store. This is
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the same as computing the supremum and equating the expression to that
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supremum.
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@item bb_inf(+@var{Ints},+@var{Expression},-@var{Inf},-@var{Vertext},+@var{Eps})
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Computes the infimum of @var{Expression} within the current constraint
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store, with the additional constraint that in that infimum, all
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variables in @var{Ints} have integral values. @var{Vertex} will contain
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the values of @var{Ints} in the infimum. @var{Eps} denotes how much a
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value may differ from an integer to be considered an integer. E.g. when
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@var{Eps} = 0.001, then X = 4.999 will be considered as an integer (5 in
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this case). @var{Eps} should be between 0 and 0.5.
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@item bb_inf(+@var{Ints},+@var{Expression},-@var{Inf})
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The same as bb_inf/5 but without returning the values of the integers
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and with an eps of 0.001.
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@item dump(+@var{Target},+@var{Newvars},-@var{CodedAnswer})
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Returns the constraints on @var{Target} in the list @var{CodedAnswer}
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where all variables of @var{Target} have veen replaced by @var{NewVars}.
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This operation does not change the constraint store. E.g. in
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@example
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dump([X,Y,Z],[x,y,z],Cons)
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@end example
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@var{Cons} will contain the constraints on @var{X}, @var{Y} and
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@var{Z} where these variables have been replaced by atoms @code{x}, @code{y} and @code{z}.
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@end table
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@node CLPR Syntax, CLPR Unification, CLPR Solver Predicates, CLPR
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@section Syntax of the predicate arguments
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@c =============================================
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The arguments of the predicates defined in the subsection above are
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defined in the following table. Failing to meet the syntax rules will
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result in an exception.
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@example
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<Constraints> ---> <Constraint> \\ single constraint \\
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| <Constraint> , <Constraints> \\ conjunction \\
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| <Constraint> ; <Constraints> \\ disjunction \\
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<Constraint> ---> <Expression> @{<@} <Expression> \\ less than \\
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| <Expression> @{>@} <Expression> \\ greater than \\
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| <Expression> @{=<@} <Expression> \\ less or equal \\
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| @{<=@}(<Expression>, <Expression>) \\ less or equal \\
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| <Expression> @{>=@} <Expression> \\ greater or equal \\
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| <Expression> @{=\=@} <Expression> \\ not equal \\
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| <Expression> =:= <Expression> \\ equal \\
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| <Expression> = <Expression> \\ equal \\
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<Expression> ---> <Variable> \\ Prolog variable \\
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| <Number> \\ Prolog number (float, integer) \\
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| +<Expression> \\ unary plus \\
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| -<Expression> \\ unary minus \\
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| <Expression> + <Expression> \\ addition \\
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| <Expression> - <Expression> \\ substraction \\
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| <Expression> * <Expression> \\ multiplication \\
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| <Expression> / <Expression> \\ division \\
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| abs(<Expression>) \\ absolute value \\
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| sin(<Expression>) \\ sine \\
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| cos(<Expression>) \\ cosine \\
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| tan(<Expression>) \\ tangent \\
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| exp(<Expression>) \\ exponent \\
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| pow(<Expression>) \\ exponent \\
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| <Expression> @{^@} <Expression> \\ exponent \\
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| min(<Expression>, <Expression>) \\ minimum \\
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| max(<Expression>, <Expression>) \\ maximum \\
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@end example
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@node CLPR Unification, CLPR Non-linear Constraints, CLPR Syntax, CLPR
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@section Use of unification
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Instead of using the @code{@{@}/1} predicate, you can also use the standard
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unification mechanism to store constraints. The following code samples
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are equivalent:
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@table @option
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@item Unification with a variable
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@example
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@{X =:= Y@}
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@{X = Y@}
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X = Y
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@end example
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@item Unification with a number
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@example
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@{X =:= 5.0@}
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@{X = 5.0@}
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X = 5.0
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@end example
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@end table
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@node CLPR Non-linear Constraints, , CLPR Unification, CLPR
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@section Non-Linear Constraints
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@c ==================================
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In this version, non-linear constraints do not get solved until certain
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conditions are satisfied. We call these conditions the isolation axioms.
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They are given in the following table.
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@example
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A = B * C when B or C is ground or // A = 5 * C or A = B * 4 \\
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A and (B or C) are ground // 20 = 5 * C or 20 = B * 4 \\
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A = B / C when C is ground or // A = B / 3
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A and B are ground // 4 = 12 / C
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X = min(Y,Z) when Y and Z are ground or // X = min(4,3)
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X = max(Y,Z) Y and Z are ground // X = max(4,3)
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X = abs(Y) Y is ground // X = abs(-7)
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X = pow(Y,Z) when X and Y are ground or // 8 = 2 ^ Z
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X = exp(Y,Z) X and Z are ground // 8 = Y ^ 3
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X = Y ^ Z Y and Z are ground // X = 2 ^ 3
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X = sin(Y) when X is ground or // 1 = sin(Y)
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X = cos(Y) Y is ground // X = sin(1.5707)
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X = tan(Y)
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@end example
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