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Detect Surprises
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Classroom Contents
Steps Toward Robust Artificial Intelligence - Thomas G Dietterich, Oregon State University
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- 1 Intro
- 2 STEPS TOWARD ROBUST ARTIFICIAL INTELLIGENCE
- 3 Marvin Minsky (1927-2016)
- 4 Minsky: Difference between Computer Programs and People
- 5 Outline
- 6 Self-Driving Cars
- 7 Automated Surgical Assistants
- 8 Autonomous Weapons
- 9 Conclusion
- 10 Robustness Lessons from Biology
- 11 Decision Making under Uncertainty
- 12 Robustness to Downside Risk
- 13 Robust Optimization • Many Al reasoning problems can be formulated as optimization problems
- 14 Impose a Budget on the Adversary
- 15 Detect Surprises
- 16 Monitor Auxiliary Regularities
- 17 Monitor Auxiliary Tasks
- 18 Open Category Object Recognition
- 19 Prediction with Anomaly Detection
- 20 Theoretical Guarantee
- 21 Related Efforts
- 22 Use a Bigger Model The risk of Unknown Unknowns may be reduced if we model more aspects of the world • Knowledge Base Construction Information Extraction & Knowledge Base Population
- 23 Use Causal Models
- 24 Employ a Portfolio of Models
- 25 Portfolio Methods in SAT & CSP
- 26 Summary
