By using Proximal Policy Optimization (PPO) algorithm introduced in the paper Proximal Policy Optimization Algorithms paper, we've trained a Mario playing agent in gym environment.
With the script, you can Test the model through python test.py. e.g. python test.py --world 1 --stage 2.
Note: If the render is too fast, append env.render() in test.py with time.sleep(0.5). It is recommended to use gym environment that supports old step-API as well.
P.s.: We shared our work of algorithms that we tried earlier in the report.