Constraint logic programming
Constraint logic programming is a form of constraint programming, in which logic programming is extended to include concepts from constraint satisfaction. A constraint logic program is a logic program that contains constraints in the body of clauses. An example of a clause including a constraint is <span class="nv">A</span><span class="p">(</span><span class="nv">X</span><span class="p">,</span><span class="nv">Y</span><span class="p">)</span> <span class="p">:-</span> <span class="nv">X</span><span class="o">+</span><span class="nv">Y</span><span class="o">></span><span class="mi">0</span><span class="p">,</span> <span class="nv">B</span><span class="p">(</span><span class="nv">X</span><span class="p">),</span> <span class="nv">C</span><span class="p">(</span><span class="nv">Y</span><spa
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- enConstraint logic programming is a form of constraint programming, in which logic programming is extended to include concepts from constraint satisfaction. A constraint logic program is a logic program that contains constraints in the body of clauses. An example of a clause including a constraint is <span class="nv">A</span><span class="p">(</span><span class="nv">X</span><span class="p">,</span><span class="nv">Y</span><span class="p">)</span> <span class="p">:-</span> <span class="nv">X</span><span class="o">+</span><span class="nv">Y</span><span class="o">></span><span class="mi">0</span><span class="p">,</span> <span class="nv">B</span><span class="p">(</span><span class="nv">X</span><span class="p">),</span> <span class="nv">C</span><span class="p">(</span><span class="nv">Y</span><spa
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- enConstraint logic programming is a form of constraint programming, in which logic programming is extended to include concepts from constraint satisfaction. A constraint logic program is a logic program that contains constraints in the body of clauses. An example of a clause including a constraint is <span class="nv">A</span><span class="p">(</span><span class="nv">X</span><span class="p">,</span><span class="nv">Y</span><span class="p">)</span> <span class="p">:-</span> <span class="nv">X</span><span class="o">+</span><span class="nv">Y</span><span class="o">></span><span class="mi">0</span><span class="p">,</span> <span class="nv">B</span><span class="p">(</span><span class="nv">X</span><span class="p">),</span> <span class="nv">C</span><span class="p">(</span><span class="nv">Y</span><span class="p">)</span>. In this clause, <span class="nv">X</span><span class="o">+</span><span class="nv">Y</span><span class="o">></span><span class="mi">0</span> is a constraint; A(X,Y), B(X), and C(Y) are literals as in regular logic programming. This clause states one condition under which the statement A(X,Y) holds: X+Y is greater than zero and both B(X) and C(Y) are true. As in regular logic programming, programs are queried about the provability of a goal, which may contain constraints in addition to literals. A proof for a goal is composed of clauses whose bodies are satisfiable constraints and literals that can in turn be proved using other clauses. Execution is performed by an interpreter, which starts from the goal and recursively scans the clauses trying to prove the goal. Constraints encountered during this scan are placed in a set called constraint store. If this set is found out to be unsatisfiable, the interpreter backtracks, trying to use other clauses for proving the goal. In practice, satisfiability of the constraint store may be checked using an incomplete algorithm, which does not always detect inconsistency.
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