The Seven Definitions of Learning
first:
- **Learning is adjusting the parameters of an internal model through the prediction error. **
- The human brain is a fantastic statistician and way better than any machine.
second:
- 86 billion neurons with 10 000 synaptic connections each
- the brain breaks down problems by creating a hirachie of multi-level models (like in listening to language)
⇒ Denk-Hierachie
third:
- each layer can only discover a small part of reality but together the layers in the brain form a very powerful learning device.
- through the prediction error the brain always guesses what happens next and through a error the brain corrects its previous assumption to the right direction. Therefore every error delivers valuable information
forth:
- randomly chosing parameters you can improve the robustness of learning
fifth:
- Am I winning or losing? We constantly evaluate our chances of winning, so we also avoid actions which are more likely to make us lose
- chess players train themselves by playing against themselves. As AlphaGo AI learns the best when playing against itself so the winning strategy strengthens while the losing strategy weakens.
- we get better at discussing when someone else imitates our arguments
⇒ Sind wir am Gewinnen
sixth:
- We learn from everything we have seen or done and we use the learned stuff to predict new situations
⇒ Prediction Error
seventh:
- what I learned in one place can be generalised everywhere else
- the more innate assumptions there are, the faster learning is
- learning always starts from a set of priori hypotheses and the system selects those best suited to the current environment.
- “To learn is to eliminate” - Jean-Pierre Changeux
see also
Tags: neuroscience science
Superlink: 050 🧠Neuroscience
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Chapter 1 Seven Defintions of Learning
Erstellt: 27-04-22 13:07