QLearner is now open source and available on Github.com.  Currently, there are only a few machine learning algorithms on the platform - namely QLearning and Approximate QLearning.  I'm hoping that having it more easily accessible on Github will encourage others to contribute and add to the project.


 QLearner provides generalized machine learning algorithms to solve to any problem defined by a QState.  The QState Plugins Template download includes a template to build your own QStates and several examples to learn from.  For more advanced users, new QAlgos can also be created to leverage the framework provided by QLearner.  Documentation and API are provided for developing your own plugins, so that it is not necessary to actually modify the source code of the underlying QLearner framework.  Additionally, QLearner can be compiled or included as a class library for instantiating instances of QLearner's algos for your own code projects.

 To use QLearner, simply open the QLearner program and click on the QState box to select a problem to solve and the QAlgo box to choose an algorithm to solve it with.  Press Learn to give QLearner a chance to "practice" at the problem and learn about it.  Press Awaken for QLearner to apply its most current knowledge to solve the problem in the most efficient way it currently knows how.  To use QLearner programatically, include QLearner as a resource in your project and instantiate QAgent objects with instances of QState and QAlgo through QAgent's Learn/Awaken methods.

 QLearner can be made to perpetually learn and continue solving an ongoing problem (such as world domination, the stock market, or the weather) if the QState Plugin is designed in such a way such that the IsEnd() state is never reached.

 About QLearner:

 QLearner was originally a short AI script built into Tech Trader for optimizing stock trading strategies.  I went ahead and took the script out of Tech Trader and made QLearner a stand-alone program so that it has more flexibility to work besides just strategy optimization for stocks.  Namely, it can now apply machine learning to any situation the user builds a template for (or finds a template for...).

 Like the name suggests, QLearner originally used Q-Learning algorithms, which is on the simpler side of AI but can still solve a lot of things and be useful in a lot of situations.  From there, more QStates and QAlgos were added.  The open-ended nature of the QLearner program though allows this to continue to be expanded on in the future.  We'll see.

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Ripple Labs' data API is now accessible as a data source in my Tech Trader platform for automated trading and backtesting, meaning you can now apply technical analysis and other chart-based trading strategies on Ripple and Bitcoin.  Many of the existing automated strategies I have for the stock market work directly on the new data with no change.  Previously the base platform only included Yahoo data sources for loading equities and indexes (though that didn't mean you couldn't load plugins for other data sources), but now the base platform also includes the Ripple data source by default for loading currencies, both fiat and cryptocurrencies.  

To load a chart on XRP, just enter XRP or XRP/USD in the symbol field.  For Bitcoin, use BTC or BTC/USD.  Follow the same format for any other currency pairs as well.

The Ripple code is also available as a separate open-source Ripple plugin for those curious or wanting to expand on the code.  I spent about a month figuring out the API docs from Ripple Labs before finally finding out the code examples were wrong and just used standard JSON code instead.

I'll be working on adding direct trading capability into the Ripple plugin as well, so that automated strategies (or the plain Manual Trade button) from Tech Trader will route trades directly your Ripple Wallet.

You can also see live charts generated and cached by Tech Trader at a simple website I created here: https://cryptocurrencies.techtrader.ai/

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Spent all weekend working on an animated version of film/graphic-oriented business card I made a few years back.  Been a long time since I last did any visual effects, but I'm pretty happy with it.  Can't wait to see this put to use... Step one to world domination.  Bahaha!

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Was going to do a more ambitious song for Halloween, but alas I ran out of ideas and just twisted one of my happier songs into something evil instead.  

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A very slow start to what should be one of my more interesting projects in a while.  Still just coming up with piano drafts for now to build a base from before making it more orchestral, but it seems like the piano alone holds up pretty well.  Sadly, my downed mood lately has somewhat found its way into what should have been very a cheerful song.  I guess it adds more dynamic at least.

I'm starting to worry about playing to time or matching a set tempo a lot less; it seems to sound better when I just play freely.  As usual, the main limitation is my left hand.  Any suggestions on chords, melodies, and other stuff welcome though.

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