7:00 – 5:00 ASRC GEOS

- Started to fold Wayne’s comments in
- Working on the Kauffman section
- Tried making it so K can be higher than N with resampling and I still can’t keep the system from converging, which makes me think that there is something wrong with the code.
- Still working on getting the algorithm right. Fitness is calculated by get_value(), but the history needs to be the genome
- Still not right, but I found this, which might help? Circuits, Attractors and Reachability in Mixed-K Kauffman Networks
- In mathematics, a
**finite field**or**Galois field**(so-named in honor of Évariste Galois) is a field that contains a finite number of elements. As with any field, a finite field is a set on which the operations of multiplication, addition, subtraction and division are defined and satisfy certain basic rules. The most common examples of finite fields are given by the integers mod*p*when*p*is a prime number.

- Send reviews to Antonio – done
- Back to work on the physics model. Make sure to include a data dictionary mapping system to support Bruce’s concept
- Sent links to Panda3D to Vadim
- Code autocompletion using deep learning
- A lot of flailing today but no good progress: