Exploiting Generative AI to Scale up Intelligent Tutoring Systems
Jakubův, Jan, Chvalovský, Karel, Goertzel, Zarathustra, Kaliszyk, Cezary, Olšák, Mirek, Piotrowski, Bartosz, Schulz, Stephan, Suda, Martin 等 9 位
Czech Technical University in Prague Universität Innsbruck Food Research Institute Prague Institut des Hautes Études Scientifiques
内容与影响
As a present to Mizar on its 50th anniversary, we develop an AI/TP system that automatically proves about 60% of the Mizar theorems in the hammer setting. We also automatically prove 75% of the Mizar theorems when the automated provers are helped by using only the premises used in the human-written Mizar proofs. We describe the methods and large-scale experiments leading to these results. This includes in particular the E and Vampire provers, their ENIGMA and Deepire learning modifications, a number of learning-based premise selection methods, and the incremental loop that interleaves growing a corpus of millions of ATP proofs with training increasingly strong AI/TP systems on them. We also present a selection of Mizar problems that were proved automatically.
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计算机 / AINatural Language Processing Techniques
Topic Modeling · Multimodal Machine Learning Applications
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