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In this contribution we propose a variant of a resolution theorem prover which selects resolution steps based on the proportion of models a newly generated clause satisfies compared to all models given in a reference class, which is generated from a subset of the initial clause set. Since the empty clause does not satisfy any models preference is given to… (More)

- Seungyeob Choi
- AIMSA
- 2002

Semantic goal-directed forward reasoning is a three stage procedure. In the first stage a reference set of models is generated from the negated theorem. In the second stage the assumption clause set is refined to a set which has an as small set of models as possible in common with the negated theorem with respect to the reference set of models. In the last… (More)

Proof planning is a form of theorem proving in which the proving procedure is viewed as a planning process. The plan operators in proof planning are called methods. In this paper we propose a strategy for heuristically restricting the set of methods to be applied in proof search. It is based on the idea that the plausibility of a method can be estimated by… (More)

- Seungyeob Choi, Manfred Kerber
- Australian Joint Conference on Artificial…
- 2002

In this contribution we present a variant of a resolution theorem prover which selects resolution steps based on the proportion of models a newly generated clause satisfies compared to all models given in a reference class. This reference class is generated from a subset of the initial clause set. Since the empty clause does not satisfy any models ,… (More)

Proof planning is an application of AI-planning in mathematical domains. The planning operators, called methods, encode proving steps. One of the strength of proof planning comes from the usage of mathematical knowledge that heuristically restricts the search space. Semantically guided proof planning uses semantic information as search control heuristics.… (More)

- Seungyeob Choi
- 2007

The goal-directed forward reasoning is a two step procedure in which the rst step generates a simpliied assumption clause set (or a single assumption clause) that semantically connicts with the negated conclusion, and the second step searches for a refutation between the simpliied assumption and the negated conclusion. In order to form a simpliied… (More)

Proof planning is an application of AI-planning in mathematical domains. The planning operators, called methods, encode proving steps. One of the strength of proof planning comes from the usage of mathematical knowledge that heuristically restricts the search space. Semantically guided proof planning takes a diierent perspective and uses semantic… (More)

There have been many attempts to use semantic information as search heuris-tics in mathematical theorem proving. In existing approaches, the semantic information is typically either given by the user or generated from intermediate formulas, and used to check the suitability of a candidate branch of the search tree. In this thesis, an initiative of using… (More)

As machine-oriented approaches to automated theorem proving are apparently revealing limitations , human-oriented approaches ooer the chance to overcome some of these limitations for many problem domains. Proof planning is the best studied approach to human-oriented theorem proving. As in any search procedure, the key problem is that we do not have a… (More)

- Seungyeob Choi
- 2002

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