To train the PG network

python train_pg.py -e 5

To visualize the results

python plot.py data/SingleAgent_05-11-2017_19-26-40 --value AverageReturn

python MAA3C.py

python MAplot.py data/MultiAgent_16-11-2017_17-06-18 --value AverageReturn1 AverageReturn2 AverageTotalReturn

Name		Name	Last commit message	Last commit date
Latest commit History 18 Commits
__pycache__		__pycache__
data		data
MAA3C.py		MAA3C.py
MASimulator.py		MASimulator.py
MAplot.py		MAplot.py
MArst_16-11-2017_17-06-18.png		MArst_16-11-2017_17-06-18.png
MultiAgentWTime_21-11-2017_17-58-44.png		MultiAgentWTime_21-11-2017_17-58-44.png
MultiAgent_16-11-2017_16-31-35.png		MultiAgent_16-11-2017_16-31-35.png
README.md		README.md
Simulator.py		Simulator.py
figure_1.png		figure_1.png
logz.py		logz.py
logz.pyc		logz.pyc
plot.py		plot.py
testMAA3C.py		testMAA3C.py
train_pg.py		train_pg.py