Primary evidence
- HOL(y)Hammer: Online ATP Service for HOL LightS1 · Primary research · Paper · 2013-09-19
Users could upload HOL Light developments and ask the service to attack new conjectures using learned relevance models, parallel ATP combinations and decision procedures.
Kaliszyk and Urban released HOL(y)Hammer as an online AI/ATP service on 19 September 2013, combining several premise-selection methods trained on project proofs with multiple automated theorem provers.
It provided an early mature example of machine learning embedded in a proof-assistant service over substantial formal mathematical libraries.
Significance rationale: HOL(y)Hammer deployed machine-learned premise selection and multiple automated reasoning systems as an online service for large HOL Light developments, bringing large-theory AI/ATP methods into routine formal mathematics workflows.
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The arXiv research record establishes the service architecture and reported HOL Light deployment.
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