LightR

LightR Sub-pages:

Version History

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Design principle

Strategy light, machine learning heavy

Central goal

Learned models -> learned systems

Planned experiments

Towards deep learning:

Multiple hand-tuned danger models -> Expert model & gate model

Hand-crafted features with naive KNN -> Search-based sequence model

Offline pre-training & online fine-tuning of everything above.

Towards differentiable programming:

Directly optimizing prior probability of getting hit (max escape angle, distancing and multi-wave risk fusion)

Per-instance level optimization of the above (Pareto frontier)