The goal of Automated Theorem Proving is to automatically generate a proof, given a conjecture (the target theorem) and a knowledge base of known facts, all expressed in a formal language. Automated Theorem Proving is useful in a wide range of applications, including the verification and synthesis of software and hardware systems.
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We present an environment, benchmark, and deep learning driven automated theorem prover for higher-order logic.
Ranked #2 on Automated Theorem Proving on HOList benchmark
We propose various machine learning tasks that can be performed on this dataset, and discuss their significance for theorem proving.
Ranked #3 on Automated Theorem Proving on HolStep (Unconditional)
Proof assistants offer a formalism that resembles human mathematical reasoning, representing theorems in higher-order logic and proofs as high-level tactics.
Ranked #1 on Automated Theorem Proving on CoqGym
Tackling Natural Language Inference with a logic-based method is becoming less and less common.
In this paper, we introduce a system called GamePad that can be used to explore the application of machine learning methods to theorem proving in the Coq proof assistant.
I propose a system for Automated Theorem Proving in higher order logic using deep learning and eschewing hand-constructed features.
Ranked #3 on Automated Theorem Proving on Metamath set.mm