Building a learning agent

Let's see how to build a learning agent that can achieve a goal. The learning agent will learn how to achieve a goal. Create a new python file and import the following package:

import argparse 
 
import gym 

Define a function to parse the input arguments:

def build_arg_parser(): 
    parser = argparse.ArgumentParser(description='Run an environment') 
    parser.add_argument('--input-env', dest='input_env', required=True, 
            choices=['cartpole', 'mountaincar', 'pendulum'],  
            help='Specify the name of the environment') 
    return parser 

Parse the input arguments:

if __name__=='__main__': 
    args = build_arg_parser().parse_args() 
    input_env = args.input_env 

Build a mapping from the input arguments to the names of the environments in the OpenAI Gym package:

    name_map = {'cartpole': 'CartPole-v0',  
                'mountaincar...