A blackboard architecture for control
Artificial Intelligence
Experiments with proof plans for induction
Journal of Automated Reasoning
Rippling: a heuristic for guiding inductive proofs
Artificial Intelligence
Knowledge-based proof planning
Artificial Intelligence
Flexibly Interleaving Processes
ICCBR '99 Proceedings of the Third International Conference on Case-Based Reasoning and Development
Cooperation of Heterogeneous Provers
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
The Use of Explicit Plans to Guide Inductive Proofs
Proceedings of the 9th International Conference on Automated Deduction
Omega: Towards a Mathematical Assistant
CADE-14 Proceedings of the 14th International Conference on Automated Deduction
Employing Theory Formation to Guide Proof Planning
AISC '02/Calculemus '02 Proceedings of the Joint International Conferences on Artificial Intelligence, Automated Reasoning, and Symbolic Computation
Roles of math search in mathematics
MKM'06 Proceedings of the 5th international conference on Mathematical Knowledge Management
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
System description: MULTI a multi-strategy proof planner
CADE' 20 Proceedings of the 20th international conference on Automated Deduction
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Humans have different problem solving strategies at their disposal and they can flexibly employ several strategies when solving a complex problem, whereas previous theorem proving and planning systems typically employ a single strategy or a hard coded combination of a few strategies. We introduce multi-strategy proof planning that allows for combining a number of strategies and for switching flexibly between strategies in a proof planning process. Thereby proof planning becomes more robust since it does not necessarily fail if one problem solving mechanism fails. Rather it can reason about preference of strategies and about failures. Moreover, our strategies provide a means for structuring the vast amount of knowledge such that the planner can cope with the otherwise overwhelming knowledge in mathematics.