Learning Module Improvements
Improvements we would like to add to the learning modules.
We have a guide on customizing learning modules here.
These are the things we would like to implement:
- Use off-object observations #numsteps #multiobj
- Implement and test rapid evidence decay as form of unsupervised memory resetting
- Improve bounded evidence performance
- Use models with fewer points
- Test particle-filter-like resampling of hypothesis space
- Re-anchor hypotheses for robustness to noise and distortions
- Less dependency on first observation
- Deal with incomplete models
- Deal with moving objects
- Support scale invariance
- Improve handling of symmetry
- Use Better Priors for Hypothesis Initialization
- Learn hot spots on objects
- Include State in Models
- Include State in Hypotheses
- Event Detection to Reset Timer
- Speed Detection to Adjust Timer
Please see the instructions here if you would like to tackle one of these tasks.
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Updated 16 days ago
