you can construct other environments in similar way constructing learning agent with python for building reinforcement learning agentwe will be using the openai gym package as shownimport gym env gym make('cartpole- 'for in range( )observation env reset(for in range( )env render(print(observationaction env action_space sample(observationrewarddoneinfo env step(actionif doneprint("episode finished after {timestepsformat( + )break observe that the cartpole can balance itself