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Ω-ANTS -- An open approach at combining Interactive and Automated Theorem Proving
- IN PROC. OF CALCULEMUS-2000. AK PETERS
, 2000
"... We present the Ω-Ants theorem prover that is built on top of an agent-based command suggestion mechanism. The theorem prover inherits beneficial properties from the underlying suggestion mechanism such as run-time extendibility and resource adaptability. Moreover, it supports the distributed integ ..."
Abstract
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Cited by 34 (23 self)
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We present the Ω-Ants theorem prover that is built on top of an agent-based command suggestion mechanism. The theorem prover inherits beneficial properties from the underlying suggestion mechanism such as run-time extendibility and resource adaptability. Moreover, it supports the distributed integration of external reasoning systems. We also introduce some notions that need to be considered to check completeness and soundness of such a system with respect to an underlying calculus.
Combined reasoning by automated cooperation
- JOURNAL OF APPLIED LOGIC
, 2008
"... Different reasoning systems have different strengths and weaknesses, and often it is useful to combine these systems to gain as much as possible from their strengths and retain as little as possible from their weaknesses. Of particular interest is the integration of first-order and higher-order tech ..."
Abstract
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Cited by 9 (6 self)
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Different reasoning systems have different strengths and weaknesses, and often it is useful to combine these systems to gain as much as possible from their strengths and retain as little as possible from their weaknesses. Of particular interest is the integration of first-order and higher-order techniques. First-order reasoning systems, on the one hand, have reached considerable strength in
some niches, but in many areas of mathematics they still cannot reliably solve relatively simple problems, for example, when
reasoning about sets, relations, or functions. Higher-order reasoning systems, on the other hand, can solve problems of this kind
automatically. But the complexity inherent in their calculi prevents them from solving a whole range of problems. However, while
many problems cannot be solved by any one system alone, they can be solved by a combination of these systems.
We present a general agent-based methodology for integrating different reasoning systems. It provides a generic integration
framework which facilitates the cooperation between diverse reasoners, but can also be refined to enable more efficient, specialist
integrations. We empirically evaluate its usefulness, effectiveness and efficiency by case studies involving the integration of first-
order and higher-order automated theorem provers, computer algebra systems, and model generators.

