Proof Construction by Tactic Learning

Author: Lasse Blaauwbroek

Paper Information

Title:Proof Construction by Tactic Learning
Authors:Lasse Blaauwbroek
Proceedings:Coq Abstracts
Editor: Nicolas Tabareau
Keywords:Tactics, Machine Learning, Proof Search

ABSTRACT. We present some early work being done to utilize Artificial Intelligence for proof search in the Coq theorem prover. In a similar vein as the TacticToe project for HOL4, we are working on a system that finds proofs of goals on the tactic level, by learning from previous tactic scripts. Learning on the level of tactics has several advantages over more low-level approaches. First, this allows for much coarser proof steps, meaning that during proof search more complicated proofs can be found. Second, it allows for the usage of custom built, domain specific tactics that where previously defined and used in the development. This will allow for better performance of the system in very specialized domains. The rest of this abstract will describe the required components of our system. Since a number of technical issues need to be addressed, we hope to solicit feedback from the Coq developers at the workshop.

Talk:Jul 08 17:30 (Session 42B)