A general purpose Q-Learning Reinforced Learning Framework.
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NN_SolarPredictor
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README.md
q_learning_with_discount_factor.py

README.md

#QLB - Q Learning Based Optimal Energy Management Bot. The standalone python file funcitons using the data generated NN_Solar_Predictor folder. It can also be tweaked to run your own Q-learning RL algorithms.

##Required It is implemented in python 2.7. It contains an example which will put you on track for twisting the framework to suit your purpose.

####Numpy

####Pylab

##Conference Publications The example used to teach Q-learning RL algorithm is taking up the task to teaching an agent when to charge or discharge a battery. It also houses a neural network trainer and predictor for solar power output in matlab.

Leo, R.; Milton, R.S.; Sibi, S., ”Reinforcement learning for optimal energy management of a solar microgrid,” Global Humanitarian Technology Conference - South Asia Satellite (GHTC-SAS), 2014 IEEE vol., no., pp.183,188, 26-27 Sept.