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Validation Testing of Autonomous Learning Systems
Author(s) -
Collopy Paul,
Sitterle Valerie,
Petrillo Jennifer
Publication year - 2020
Publication title -
insight
Language(s) - English
Resource type - Journals
eISSN - 2156-4868
pISSN - 2156-485X
DOI - 10.1002/inst.12285
Subject(s) - field (mathematics) , computer science , test (biology) , artificial intelligence , systems engineering , software engineering , engineering , mathematics , paleontology , pure mathematics , biology
Validating artificial intelligence systems is challenging. Systems continuing to learn new behaviors in the field are particularly difficult, because the designer does not know what the functions need proving. This article reports on a research project using the Toulmin augmentation method to structure validation test plans and validation testing for very difficult systems like field‐learning AI.