Abstract
One quality that makes biological systems appear intelligent is their robustness to difficult circumstances. Robustness is crucial to intelligent behavior and important to AI research. We distinguish between ante-failure and post-failure robustness for causal tasks. Ante-failure robust systems resist failure, whereas post-failure systems incorporate the ability to recover from failure once it happens. We point out the power of post-failure robustness in AI problems, closely examining one example in visual motion tracking. Finally, we raise theoretical issues and argue for greater effort towards building post-failure robust systems.
Original language | English (US) |
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Pages | 3-9 |
Number of pages | 7 |
State | Published - 1997 |
Externally published | Yes |
Event | Proceedings of the 1997 14th National Conference on Artificial Intelligence, AAAI 97 - Providence, RI, USA Duration: Jul 27 1997 → Jul 31 1997 |
Other
Other | Proceedings of the 1997 14th National Conference on Artificial Intelligence, AAAI 97 |
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City | Providence, RI, USA |
Period | 7/27/97 → 7/31/97 |
ASJC Scopus subject areas
- Software
- Artificial Intelligence