Work

Toward verified artificial intelligence

Year: 2022

Type: article

Abstract: Making AI more trustworthy with a formal methods-based approach to AI system verification and validation.

Source: Communications of the ACM

DOI: 10.1145/3503914

Authors: Sanjit A. Seshia, Dorsa Sadigh, S. Shankar Sastry

Institutions: University of California, Berkeley, Stanford University

Language: English

Topic: Formal Methods in Verification

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: National Science Foundation, Semiconductor Research Corporation, Defense Advanced Research Projects Agency, Advanced Research Projects Agency

Awards: CPS: Frontier: Collaborative Research: VeHICaL: Verified Human Interfaces, Control, and Learning for Semi-Autonomous Systems, G8763469402

OpenAlex ID: W4283212640

FWCI: 31.81

Cites: 30

Cited by: 253

Related to: 10