Basic MonteCarlo search algorithms as described in page 673
http://www.jair.org/papers/paper3484.html

### Requirements
git clone https://github.com/openai/gym
cd gym
pip install -e . # minimal install

QValueFunction uses linear approximation of the Q function applied to Mountain Car problem

• mc_search.py (please run this file)
• QValueFunction.py
• util.py

QValueFunction uses Theanets Regressor as function approximator applied to Mountain Car problem

• mc_search_theanets.py (please run this file)
• QNetwork_theanets.py
• util.py

Reference benchmark using random choice on every step.

• Pendulum_baseline.py (please run this file)

QValueFunction uses Theanets Regressor as function approximator applied to Pendulum problem

• Pend_mc_search_theanets.py (please run this file)
• Pend_QNetwork_theanets.py
• util.py