A smaller improvement is obtained by evolving targetted E prover strategies on two particular premise selections, using the Blind Strategymaker (BliStr) system.

May 26, 2013 · This results in 16% improvement (39.0% to 45.5% Flyspeck problems solved) of the overall strength of the service when using 14 CPUs and 30 ...

Several schemes for frequency-based feature weighting are explored in combination with distanceweighted k-nearest-neighbor classier to improve the strength ...

This results in 16% improvement (39.0% to 45.5% Flyspeck problems solved) of the overall strength of the service when using 14 CPUs and 30 seconds. The best ...

Two complementary AI methods are used to improve the strength of the AI/ATP service for proving conjectures over the HOL Light and Flyspeck corpora.

Bibliographic details on Stronger Automation for Flyspeck by Feature Weighting and Strategy Evolution.

Stronger Automation for Flyspeck by Feature Weighting and Strategy Evolution · Cezary Kaliszyk and Josef Urban. Abstract. Two complementary AI methods are used ...

Stronger automation for Flyspeck by feature weighting and strategy evolution. In J. C. Blanchette and J. Urban, editors, PxTP 2013, volume 14 of EPiC Series ...

Stronger automation for Flyspeck by feature weighting and strategy evolution. In J. C. Blanchette and J. Urban, editors, PxTP 2013, volume 14 of EPiC Series ...

Oct 14, 2024 · (2013): Stronger Automation for Flyspeck by Feature Weighting and Strategy Evolution; Kaliszyk, Cezary et al. (2014): Learning-Assisted ...