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2010 International Conference on Artificial Intelligence and Computational Intelligence
A Scenario-Based Method for Safety Certification of Artificial Intelligent Software
Sanya, China
October 23-October 24
ISBN: 978-0-7695-4225-6
| ASCII Text | x | ||
| Guoqi Li, Minyan Lu, Bin Liu, "A Scenario-Based Method for Safety Certification of Artificial Intelligent Software," Artificial Intelligence and Computational Intelligence, International Conference on, vol. 3, pp. 481-483, 2010 International Conference on Artificial Intelligence and Computational Intelligence, 2010. | |||
| BibTex | x | ||
| @article{ 10.1109/AICI.2010.339, author = {Guoqi Li and Minyan Lu and Bin Liu}, title = {A Scenario-Based Method for Safety Certification of Artificial Intelligent Software}, journal ={Artificial Intelligence and Computational Intelligence, International Conference on}, volume = {3}, year = {2010}, isbn = {978-0-7695-4225-6}, pages = {481-483}, doi = {http://doi.ieeecomputersociety.org/10.1109/AICI.2010.339}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Artificial Intelligence and Computational Intelligence, International Conference on TI - A Scenario-Based Method for Safety Certification of Artificial Intelligent Software SN - 978-0-7695-4225-6 SP481 EP483 A1 - Guoqi Li, A1 - Minyan Lu, A1 - Bin Liu, PY - 2010 KW - software trustability KW - intelligent systems KW - software engineering VL - 3 JA - Artificial Intelligence and Computational Intelligence, International Conference on ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AICI.2010.339
Artificial intelligence (AI) is attractive for safety critical fields. However, there have been few success cases, for the AI technique is usually lack of determinism and predictability, which is usually regarded as a disqualifier in a safety on text. Increased researches and supererogatory efforts are providing to incorporate AI into the safety-critical systems in recent years. In this paper, we present a scenario-based method for safety certification, with the method AI modules of system could be evaluated before invoked, if its trust ability is satisfied, then the program will be performed for safety critical systems, otherwise it will be terminated to ask human assistance or postpone the missions.
Index Terms:
software trustability, intelligent systems, software engineering
Citation:
Guoqi Li, Minyan Lu, Bin Liu, "A Scenario-Based Method for Safety Certification of Artificial Intelligent Software," aici, vol. 3, pp.481-483, 2010 International Conference on Artificial Intelligence and Computational Intelligence, 2010
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