What every computer scientist should know about floating-point arithmetic
ACM Computing Surveys (CSUR)
ILPS '94 Proceedings of the 1994 International Symposium on Logic programming
Guaranteed tuning, with application to robust control and motion planning
Automatica (Journal of IFAC)
Nonlinear control system design by quantifier elimination
Journal of Symbolic Computation - Special issue: applications of quantifier elimination
Robust multi-objective feedback design by quantifier elimination
Journal of Symbolic Computation - Special issue: applications of quantifier elimination
Robust analysis and design of control systems using interval arithmetic
Automatica (Journal of IFAC)
Approximation Techniques for Non-linear Problems with Continuum of Solutions
Proceedings of the 5th International Symposium on Abstraction, Reformulation and Approximation
Extending Consistent Domains of Numeric CSP
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Interval constraint solving for camera control and motion planning
ACM Transactions on Computational Logic (TOCL)
A branch and prune algorithm for the approximation of non-linear AE-solution sets
Proceedings of the 2006 ACM symposium on Applied computing
Efficient solving of quantified inequality constraints over the real numbers
ACM Transactions on Computational Logic (TOCL)
Inner and outer approximations of existentially quantified equality constraints
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
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This paper introduces a new algorithm for solving a subclass of quantified constraint satisfaction problems (QCSP) where existential quantifiers precede universally quantified inequalities on continuous domains. This class of QCSPs has numerous applications in engineering and design. We propose here a new generic branch and prune algorithm for solving such continuous QCSPs. Standard pruning operators and solution identification operators are specialized for universally quantified inequalities. Special rules are also proposed for handling the parameters of the constraints. First experimentation show that our algorithm outperforms the state of the art methods.