In this paper we address assertion retrieval and application in theorem proving systems or proof planning systems for classical first-order logic. Due to Huang the notion of assertion comprises mathematical knowledge such as definitions, theorems, and axioms. We propose a distributed mediator module between a mathematical knowledge base KB and a theorem proving system TP which is independent of the particular proof representation format of TP and which applies generalised resolution in order to analyse the logical consequences of arbitrary assertions for a proof context at hand. Our approach is applicable also to the assumptions which are dynamically created during a proof search process. It therefore realises a crucial first step towards f...
In this contribution I advocate an open system for formalised mathematical reasoning that is able to...
Logic programming languages have many characteristics that indicate that they should serve as good i...
In this paper we present a framework for automated learning within mathematical reasoning systems. I...
In this paper we address assertion retrieval and application in theorem proving systems or proof pla...
Our work addresses assertion retrieval and application in theorem proving systems or proof planning ...
For nearly two decades human-oriented theorem proving techniques have been in the focus of interest ...
This paper is an overview of a variety of results, all centered around a common theme, namely embedd...
We transform a user-friendly formulation of aproblem to a machine-friendly one exploiting the variab...
This thesis focuses on implementation of resolution-based automatic theorem prover for propositional...
Research on automated and interactive theorem proving aims at the mechanization of logical reasoning...
In this thesis we develop a comprehensive human-oriented theorem proving system that integrates seve...
In this paper we propose a context-based approach to abstract theorem proving. The challenges stem f...
The proofs generated by clausa reasoners are often too long and hard to follow by the user (even if ...
Abstract. In this paper we propose how proof planning systems can be extended by an automated learni...
[Symbolic and algebraic manipulation]: Symbolic and algebraic algorithms—Theorem proving algorithms;...
In this contribution I advocate an open system for formalised mathematical reasoning that is able to...
Logic programming languages have many characteristics that indicate that they should serve as good i...
In this paper we present a framework for automated learning within mathematical reasoning systems. I...
In this paper we address assertion retrieval and application in theorem proving systems or proof pla...
Our work addresses assertion retrieval and application in theorem proving systems or proof planning ...
For nearly two decades human-oriented theorem proving techniques have been in the focus of interest ...
This paper is an overview of a variety of results, all centered around a common theme, namely embedd...
We transform a user-friendly formulation of aproblem to a machine-friendly one exploiting the variab...
This thesis focuses on implementation of resolution-based automatic theorem prover for propositional...
Research on automated and interactive theorem proving aims at the mechanization of logical reasoning...
In this thesis we develop a comprehensive human-oriented theorem proving system that integrates seve...
In this paper we propose a context-based approach to abstract theorem proving. The challenges stem f...
The proofs generated by clausa reasoners are often too long and hard to follow by the user (even if ...
Abstract. In this paper we propose how proof planning systems can be extended by an automated learni...
[Symbolic and algebraic manipulation]: Symbolic and algebraic algorithms—Theorem proving algorithms;...
In this contribution I advocate an open system for formalised mathematical reasoning that is able to...
Logic programming languages have many characteristics that indicate that they should serve as good i...
In this paper we present a framework for automated learning within mathematical reasoning systems. I...