I’ve started work on replacing MAM’s over-complex dynamic patching with a python (pyx) external. The CA-like aspect of MAM is really better suited to an OOP system than doing the work in PD. Here are the first of the system’s dreams.
The first is an early version where loops were very likely (where the same memories are retreived over and over again):
Here is a dream generated by the current version of the system which avoids these endless loops. This particular dream is quite long (30 activations) which is due to the similarity between (dark) memories. In this version the histograms of the stored images are analysed for similarity (using the same method as the SOM) in order to propagate activations to the most similar memory. The signal is degraded proportional to the distance between memories. The more similar images are the longer the dream is, due to less signal degredation. Signal degredation is not visualized in these images.
This is the SOM used to generate these dreams. It was a test running over 3 days. Due to a glitch the camera recorded while I was not expecting that resulted in many dark images.