POPL '87 Proceedings of the 14th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
CADE-10 Proceedings of the tenth international conference on Automated deduction
Logic and computation in MATHPERT: an expert system for learning mathematics
Proceedings of the third conference on Computers and mathematics
Artificial Intelligence
Rippling: a heuristic for guiding inductive proofs
Artificial Intelligence
A resolution principle for constrained logics
Artificial Intelligence
Temporal planning with continuous change
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Term rewriting and all that
Knowledge-based proof planning
Artificial Intelligence
New methods to color the vertices of a graph
Communications of the ACM
The Mathematica Book
Comparing approaches to the exploration of the domain of residue classes
Journal of Symbolic Computation - Integrated reasoning and algebra systems
JELIA '96 Proceedings of the European Workshop on Logics in Artificial Intelligence
Hauptvortrag: Quantifier elimination for real closed fields by cylindrical algebraic decomposition
Proceedings of the 2nd GI Conference on Automata Theory and Formal Languages
Constraint Model Elimination and a PTTP-Implementation
TABLEAUX '95 Proceedings of the 4th International Workshop on Theorem Proving with Analytic Tableaux and Related Methods
Automatic Generation of Epsilon-Delta Proofs of Continuity
AISC '98 Proceedings of the International Conference on Artificial Intelligence and Symbolic Computation
SoleX: A Domain-Independent Scheme for Constraint Solver Extension
AISC '98 Proceedings of the International Conference on Artificial Intelligence and Symbolic Computation
CADE-18 Proceedings of the 18th International Conference on Automated Deduction
System Description: The MathWeb Software Bus for Distributed Mathematical Reasoning
CADE-18 Proceedings of the 18th International Conference on Automated Deduction
The Use of Explicit Plans to Guide Inductive Proofs
Proceedings of the 9th International Conference on Automated Deduction
CADE-12 Proceedings of the 12th International Conference on Automated Deduction
Non-Trivial Symbolic Computations in Proof Planning
FroCoS '00 Proceedings of the Third International Workshop on Frontiers of Combining Systems
Combining linear programming and satisfiability solving for resource planning
The Knowledge Engineering Review
Bridging the gap between planning and scheduling
The Knowledge Engineering Review
Refinement planning: status and prospectus
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Proof planning with multiple strategies
Artificial Intelligence
Failure Reasoning in Multiple-Strategy Proof Planning
Electronic Notes in Theoretical Computer Science (ENTCS)
Impasse-driven reasoning in proof planning
MKM'05 Proceedings of the 4th international conference on Mathematical Knowledge Management
Reductio ad absurdum: planning proofs by contradiction
Reasoning, Action and Interaction in AI Theories and Systems
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Proof planning is an application of AI planning to theorem proving that employs plan operators that encapsulate mathematical proof techniques. Many proofs require the instantiation of variables; that is, mathematical objects with certain properties have to be constructed. This is particularly difficult for automated theorem provers if the instantiations have to satisfy requirements specific for a mathematical theory, for example, for finite sets or for real numbers, because in this case unification is insufficient for finding a proper instantiation. Often, constraint solving can be employed for this task. We describe a framework for the integration of constraint solving into proof planning that combines proof planners and stand-alone constraint solvers. Proof planning has some peculiar requirements that are not met by any off-the-shelf constraint-solving system. Therefore, we extended an existing propagation-based constraint solver in a generic way. This approach generalizes previous work on tackling the problem. It provides a more principled way and employs existing AI technology.