E-SETHEO: Design, Configuration and Use of a Parallel Automated Theorem Prover

Abstract

One of the key issues in Automated Theorem Proving is the search for optimal proof strategies. Since there is not one uniform strategy which works optimally on all proof tasks, one is faced with the difficult problem of selecting a good strategy for a given task. Strategy parallelism, where a proof task is attempted in parallel by a set of strategies with distributed resources, is a way of circumventing this strategy selection problem. However, the problem of selecting the parallel strategies and distributing the available resources among them still remains. Therefore we have developed a method for automatic strategy and resource configuration based on the combination of a genetic algorithm and a gradient procedure. For the effective use of this method it is necessary to be able to automatically gather large amounts of experimental data. We present an environment for such large scale data collection that has been used by us in preparation of the CADE-16 automatic system competition. In order to evaluate the potential of the method experimentally, we have implemented the strategy parallel theorem prover e-SETHEO. The experimental results obtained with the system already justify our approach while showing substantial potential for future development.