Current PALADIN Testing/Optimization Class Assignments Upcoming SynthNet Evolution Testing New Project (TBA)
With the Genetic Mutation Engine completed, I wanted to put it to actual use. While it’s fun to put complex SynthNet networks through the mutation process and watch the really cool looking results, manually doing it doesn’t really serve much of a purpose. However, now that the Evolution Experimentation Module is complete, the real power of the mutation engine is unlocked.
Artificial Selection in Action
The Evolution module allows us to take an initial, manually created SynthNet network (as simple or complex as desired), test how effective it is in a task, and then either allow it to reproduce and continue on its genetic line, or prevent reproduction in the case of decreased task effectiveness. It performs this across multiple “breeds”, or equally effective genomes, until a novel mutation shows improved performance, which is considered a new “species”. This, in effect, emulates multiple genetic lines competing at a user-defined task, and artificial selection based on that task dictating the path of evolution of the SynthNet network.
Specifics of the module are as follows:
I’m currently trying it out by artificially selecting for a neural network that can detect parity (even/odd) in numbers. We’ll see how it does – once I have some results, I’ll be creating the front-end user interface to browse through mutations/results/pictures on the web. Hopefully more on that soon!