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#HtmControlCenter Wiki This repository is place to store experimentation code relating to Hierarchical Temporal Memory.

##What is HTM? Hierarchical Temporal Memory is a simple model based on the neocorex in our brain. The software model can emulate our brain given Jeff Hawkins understanding as written in his book On Intelligents. There is lots of information on the internet describing HTM. A good place to start is at www.numenta.com, their git hub site has good information too.

##What does HTM do? HTM models how our brain learns sequences and patterns, both spacial and temporal.

##What does this code do? To really learn more about HTMs, I figured I needed to see the code work and try some experiments to see if it actually works. It's hard to get a good understanding of HTM from the information on the internet, getting a fair comparison to Artificial Neural Networks is very hard by only reading papers on the internet. If you are trying to understand HTMs, and what they are good for, you really need to experiment with the code. From what I have learned, HTMs are in the very early stages of R&D, there may be some cool ideas in there, but finding practical uses...may be a little ways out. This code has helped me learn what they are good at, given me some cool ideas, and helped me understand where HTMs really are.

##Where did this code come from This code was heavily seeded from a HTM implementation by Michael Ferrier (thanks!). He wrote this C++ implementation. I have ported to by Control Center code so I can experiment around in an environment that I debug easily in. Some might wonder why I didn't just start with the Numenta code, that is written in Python, it's quite complex, and encompasses a large amount of functionality. I figured I'd start with some more simple so I can get a better understanding of the base HTM ideas first. I'm also more familiar with C++, and I think long term this implementation can scale larger due to the speed of C++...I understand many would debate this.