MaLARea (a Machine Learner for Automated Reasoning) is a simple metasystem iteratively combining deductive Automated Reasoning tools (now the E and the SPASS ATP systems) with a machine learning component (now the SNoW system used in the naive Bayesian learning mode). Its intended use is in large theories, i.e. on a large number of problems which in a consistent fashion use many axioms, lemmas, theorems, definitions and symbols. The system works in cycles of theorem proving followed by machine learning from successful proofs, using the learned information to prune the set of available axioms for the next theorem proving cycle. Although the metasystem is quite simple (ca. 1000 lines of Perl code), its design already now poses quite interesting questions about the nature of thinking, in particular, about how (and if and when) to combine learning from previous experience to attack difficult unsolved problems. The first version of MaLARea has been tested on the more difficult (chainy) division of the MPTP Challenge solving 142 problems out of 252, in comparison to E’s 89 and SPASS ’ 81 solved problems. It also outperforms the SRASS metasystem, which also uses E and SPASS as components, and solves 126 problems. 1

In this paper we compare the performance of various automated theorem provers on nearly all of the theorems in loop theory known to have been obtained with the assistance of automated theorem provers. Our analysis yields some surprising results, e.g., the theorem prover most often used by loop theorists doesn’t necessarily yield the best performance. 1

An interactive ATP service is a new feature in the Mizar proof assistant. The functionality of the service is in many respects analogous to the Sledgehammer subsystem of Isabelle/HOL. The ATP service requires minimal user configuration and is accessible via a few keystrokes from within Mizar mode in Emacs. In return, for a given goal formula, the ATP service, when it succeeds, finds premises sufficient to prove the goal. The “escape ” to ATP uses a sound translation from Mizar’s language to that of first-order provers, the same translation that has been used in the more batch oriented Automated Reasoning for Mizar (MizAR) web services presented in [16]. We briefly present the interactive ATP service followed by an account of initial experiments with the tool. We claim with some confidence that the tool will substantially ease the process of preparing new Mizar articles. 1

Abstract. The vision of a computerised assistant to mathematicians has existed since the inception of theorem proving systems. The Alcor system has been designed to investigate and explore how a mathematician might interact with such an assistant by providing an interface to Mizar and the Mizar Mathematical Library. Our current research focuses on the integration of searching and authoring while proving. In this paper we use a scenario to elaborate the nature of the interaction. We abstract from this two distinct types of searching and describe how the Alcor interface implements these with keyword and LSI-based search. Though Alcor is still in its early stages of development, there are clear implications for the general problem of integrating searching and authoring, as well as technical issues with Mizar.

This paper gives an overview of the existing link between the Mizar project for formalization of mathematics and Automated Reasoning tools (mainly the Automated Theorem Provers (ATPs)). It explains the motivation for this work, gives an overview of the translation method, discusses the projects and works that are based on it, and possible future projects and directions. 1

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