playing idealized trading games with deep reinforcement learning
This repo is the code for this paper. Deep reinforcement learing is used to find optimal strategies in these two scenarios:
Several neural networks are compared:
You can get all dependencies via the Anaconda environment file, env.yml:
conda env create -f env.yml
Just call the main function
python main.py
You can play with model parameters (specified in main.py), if you get good results or any trouble, please contact me at gxiang1228@gmail.com