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Analyzing introspective predictors
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Classroom Contents
Safe Learning in Robotics
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- 1 Intro
- 2 Air Traffic Control: Separation Assurance
- 3 Growing numbers of UAV applications
- 4 Operations in unstructured environments: perceptic
- 5 Outline
- 6 Reachable Set Propagation
- 7 Level set interpretation
- 8 Numerical computation of reachable sets
- 9 Collision Avoidance Pilots instructed to attempt to collide vehicles
- 10 Backwards Reachable Set: Capture
- 11 Mode sequencing and reach-avoid
- 12 Dealing with the curse of dimensionality
- 13 Fast and Safe Planning
- 14 Precomputed Tracking Bound
- 15 10D Tracking 3D using RRT
- 16 Fast and Fast(er) Planning
- 17 Meta-Planning using FasTrack in AR/VR
- 18 Applied to: A Noisily Rational Human Model
- 19 Rationality is actually model confidence
- 20 Bayesian Model Confidence
- 21 Extending to multiple humans and robots
- 22 Analyzing introspective predictors
- 23 Using ML to compute sets
- 24 Safe Policy Gradient Reinforcement Lean
- 25 Online Disturbance Model Validation
- 26 Leaming, while staying safe
