Temporal Difference Learning in Python

Author: Jeremy Stober
Contact: stober@gmail.com
Version: 0.01

This is a Python implementation of some common temporal difference
learning algorthms. The implementations use discrete, linear, or CMAC
value function representations and include eligability traces
(ie. TD(\lambda)).

Requires: numpy, cmac (http://github.com/stober/cmac), cartpole (https://github.com/stober/cartpole), pybrain (for nfq comparison)