Reinforcement learning methodes that map continuous to continuous
Question: I am building a model where firms have to set prices and make production
decisions. Prices are continuous and so are the decision variables.
(inventory, last sales, prices...).

What reinforcement learning method can I use that maps continuous to
continuous ? Which python packages are there? If there are no python packages,
I could write a wrapper.


Answer: [PyBrain](http://pybrain.org/) machine learnign library is what you're looking
for. It is quite complex implementation of neural networks, but when you
understand it you will get a really powerful tool.

PyBrain is a python library for neural network modelling. [Overview of the
PyBrain](http://pybrain.org/) should get you a basic idea: at each timestep
you provides neural network with a set of continuous values and take out
another set of continuous values. But more important is that you can evaluate
the output and train your neural network.

All these steps - including network training - are already implemented in
PyBrain.

