The complexity of linear problems in fields
Journal of Symbolic Computation
Communications of the ACM
Partial Cylindrical Algebraic Decomposition for quantifier elimination
Journal of Symbolic Computation
The CLP( R ) language and system
ACM Transactions on Programming Languages and Systems (TOPLAS)
Journal of Symbolic Computation
Complexity and uniformity of elimination in Presburger arithmetic
ISSAC '97 Proceedings of the 1997 international symposium on Symbolic and algebraic computation
REDLOG: computer algebra meets computer logic
ACM SIGSAM Bulletin
Simplification of quantifier-free formulae over ordered fields
Journal of Symbolic Computation - Special issue: applications of quantifier elimination
Mixed real-integer linear quantifier elimination
ISSAC '99 Proceedings of the 1999 international symposium on Symbolic and algebraic computation
Linear problems in valued fields
Journal of Symbolic Computation
Computational Geometry Problems in REDLOG
Selected Papers from the International Workshop on Automated Deduction in Geometry
Essentials of Constraint Programming
Essentials of Constraint Programming
Essentials of Constraint Programming
Essentials of Constraint Programming
CLP(QS): a declarative spatial reasoning framework
COSIT'11 Proceedings of the 10th international conference on Spatial information theory
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We present an extension of constraint logic programming, where the admissible constraints are arbitrary first-order formulas over various domains: real numbers with ordering, linear constraints over p-adic numbers, complex numbers, linear constraints over the integers with ordering and congruences (parametric Presburger Arithmetic), quantified propositional calculus (parametric qsat), term algebras. Our arithmetic is always exact. For ℝ are ℂ there are no restrictions on the polynomial degree of admissible constraints. Constraint solving is realized by effective quantifier elimination. We have implemented our methods in our system clp(rl). A number of computation examples with clp(rl) are given in order to illustrate the conceptual generalizations provided by our approach and to demonstrate its feasibility.