Preprint / scholarly article
Audit-Closed AI Scientist Protocol
- Published
- DOI
- 10.5281/zenodo.18728589
Abstract
This preprint defines an audit-closed protocol for autonomous scientific discovery in self-driving laboratories under deterministic replay and public-log governance constraints, yielding trustworthy accept-reject-update decisions with always-valid sequential evidence. It integrates typed stochastic observation interfaces, e-process based testing, logged-propensity adaptive experimentation, drift recovery, and certificate-based reproducibility controls.
Keywords
- AI scientist protocol
- autonomous scientific discovery
- self-driving laboratories
- audit-closed governance
- transparency log
- incorporation certificates
- e-processes
- sequential inference
- adaptive experimentation
- drift recovery
- reproducibility
- Byzantine resilience