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63
MBase: Representing Knowledge and Context for the Integration of Mathematical Software Systems
, 2000
"... In this article we describe the data model of the MBase system, a webbased, ..."
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Cited by 49 (12 self)
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In this article we describe the data model of the MBase system, a webbased,
IsaPlanner: A prototype proof planner in Isabelle
 In Proceedings of CADE’03, LNCS
, 2003
"... Abstract. IsaPlanner is a generic framework for proof planning in the interactive theorem prover Isabelle. It facilitates the encoding of reasoning techniques, which can be used to conjecture and prove theorems automatically. This paper introduces our approach to proof planning, gives and overview o ..."
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Cited by 34 (9 self)
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Abstract. IsaPlanner is a generic framework for proof planning in the interactive theorem prover Isabelle. It facilitates the encoding of reasoning techniques, which can be used to conjecture and prove theorems automatically. This paper introduces our approach to proof planning, gives and overview of IsaPlanner, and presents one simple yet effective reasoning technique. 1
Proof Planning
 PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON AI PLANNING SYSTEMS, (AIPS
, 1996
"... We describe proof planning, a technique for the global control of search in automatic theorem proving. A proof plan captures the common patterns of reasoning in a family of similar proofs and is used to guide the search for new proofs in this family. Proof plans are very similar to the plans cons ..."
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Cited by 29 (2 self)
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We describe proof planning, a technique for the global control of search in automatic theorem proving. A proof plan captures the common patterns of reasoning in a family of similar proofs and is used to guide the search for new proofs in this family. Proof plans are very similar to the plans constructed by plan formation techniques. Some differences are the nonpersistence of objects in the mathematical domain, the absence of goal interaction in mathematics, the high degree of generality of proof plans, the use of a metalogic to describe preconditions in proof planning and the use of annotations in formulae to guide search.
AgentOriented Integration of Distributed Mathematical Services
 Journal of Universal Computer Science
, 1999
"... Realworld applications of automated theorem proving require modern software environments that enable modularisation, networked interoperability, robustness, and scalability. These requirements are met by the AgentOriented Programming paradigm of Distributed Artificial Intelligence. We argue that ..."
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Cited by 20 (10 self)
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Realworld applications of automated theorem proving require modern software environments that enable modularisation, networked interoperability, robustness, and scalability. These requirements are met by the AgentOriented Programming paradigm of Distributed Artificial Intelligence. We argue that a reasonable framework for automated theorem proving in the large regards typical mathematical services as autonomous agents that provide internal functionality to the outside and that, in turn, are able to access a variety of existing external services. This article describes...
Proof Development with ΩMEGA
 PROCEEDINGS OF THE 18TH CONFERENCE ON AUTOMATED DEDUCTION (CADE–18), VOLUME 2392 OF LNAI
, 2002
"... ..."
Automatic learning of proof methods in proof planning
 L. J. of the IGPL
, 2002
"... Our research interests in this project are in exploring how automated reasoning systems can learn theorem proving strategies. In particular, we are looking into how a proof planning system (Bundy, 1988) can automatically learn ..."
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Cited by 11 (4 self)
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Our research interests in this project are in exploring how automated reasoning systems can learn theorem proving strategies. In particular, we are looking into how a proof planning system (Bundy, 1988) can automatically learn
CaseAnalysis for Rippling and Inductive Proof
"... Abstract. Rippling is a heuristic used to guide rewriting and is typically used for inductive theorem proving. We introduce a method to support caseanalysis within rippling. Like earlier work, this allows goals containing ifstatements to be proved automatically. The new contribution is that our me ..."
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Cited by 9 (2 self)
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Abstract. Rippling is a heuristic used to guide rewriting and is typically used for inductive theorem proving. We introduce a method to support caseanalysis within rippling. Like earlier work, this allows goals containing ifstatements to be proved automatically. The new contribution is that our method also supports caseanalysis on datatypes. By locating the caseanalysis as a step within rippling we also maintain the termination. The work has been implemented in IsaPlanner and used to extend the existing inductive proof method. We evaluate this extended prover on a large set of examples from Isabelle’s theory library and from the inductive theorem proving literature. We find that this leads to a significant improvement in the coverage of inductive theorem proving. The main limitations of the extended prover are identified, highlight the need for advances in the treatment of assumptions during rippling and when conjecturing lemmas. 1
A ProofPlanning Framework with explicit Abstractions based on Indexed Formulas
 Electronic Notes in Theoretical Computer Science
, 2001
"... A major motivation of proofplanning is to bridge the gap between highlevel, cognitively adequate reasoning for specific domains, and calculuslevel reasoning to ensure soundness. For high reasoning levels the cognitive adequacy of representation and reasoning techniques is a major issue, while ..."
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Cited by 8 (5 self)
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A major motivation of proofplanning is to bridge the gap between highlevel, cognitively adequate reasoning for specific domains, and calculuslevel reasoning to ensure soundness. For high reasoning levels the cognitive adequacy of representation and reasoning techniques is a major issue, while for lower reasoning levels the adequacy wrt. the modelled domain is important. Furthermore, proof construction is an engineering task and there is a need to support the design and application of proofsearch engineering methods. To this end we present a framework to explicitly support di#erent reasoning levels. To structure reasoning levels the framework allows for an explicit representation of abstractions and proofsearch refinement techniques. In order to ensure soundness within a reasoning level, we use techniques developed in the context of matrix characterisation relying on the notion of indexed formulas. Furthermore, we introduce a uniform concept for contextual reasoning, and sketch basic tacticals for the definition of tactics to organise the overall proofsearch inside and across di#erent reasoning levels.
Proof Planning: A Fresh Start?
 In Proc. of the IJCAR 2001 Workshop: Future Directions in Automated Reasoning
, 2001
"... Proof Planning is a technique for automated (and interactive) theorem proving that searches for proof plans at the level of abstract methods. Proof methods consist of a chunk of mathematically motivated, recurring patterns of calculus level inferences with additional pre and postconditions tha ..."
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Cited by 5 (2 self)
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Proof Planning is a technique for automated (and interactive) theorem proving that searches for proof plans at the level of abstract methods. Proof methods consist of a chunk of mathematically motivated, recurring patterns of calculus level inferences with additional pre and postconditions that model their applicability conditions.