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Found 11 papers, 4 papers with code
Learning Guided Automated Reasoning: A Brief Survey
Automated theorem provers and formal proof assistants are general reasoning systems that are in theory capable of proving arbitrarily hard theorems, thus solving arbitrary problems reducible to mathematics and logical reasoning.
Learning Program Synthesis for Integer Sequences from Scratch
We present a self-learning approach for synthesizing programs from integer sequences.
Tree Neural Networks in HOL4
We present an implementation of tree neural networks within the proof assistant HOL4.
Self-Learned Formula Synthesis in Set Theory
A reinforcement learning algorithm accomplishes the task of synthesizing a set-theoretical formula that evaluates to given truth values for given assignments.
Deep Reinforcement Learning for Synthesizing Functions in Higher-Order Logic
We set a precedent for statistically guided synthesis of Diophantine equations by solving 78. 5% of the generated test problems.
GRUNGE: A Grand Unified ATP Challenge
This paper describes a large set of related theorem proving problems obtained by translating theorems from the HOL4 standard library into multiple logical formalisms.
Logic in Computer Science
Learning to Reason with HOL4 tactics
Techniques combining machine learning with translation to automated reasoning have recently become an important component of formal proof assistants.
TacticToe: Learning to Prove with Tactics
We implement a automated tactical prover TacticToe on top of the HOL4 interactive theorem prover.
Sharing HOL4 and HOL Light proof knowledge
When proving their properties, a human can often take inspiration from the existing formalized proofs available in other provers or libraries.
Premise Selection and External Provers for HOL4
Learning-assisted automated reasoning has recently gained popularity among the users of Isabelle/HOL, HOL Light, and Mizar.
