Body: <p>Some background first: My programming background is Python and C. Also, &quot;classical&quot; control systems. I.e PID control, analogue, feedback-based correction etc.</p>
  <p>Inverted pendulum is a textbook control problem. Traditionally it is solved through use of some type of algorithm, most notably PID.</p>
  <p>Recently I've discovered that a <a href="https://ai.stackexchange.com/questions/16812/can-supervised-learning-be-used-to-solve-the-inverted-pendulum-problem">number</a> of <a href="https://www.youtube.com/watch?v=5Q14EjnOJZc" rel="nofollow noreferrer">successful</a> <a href="https://www.researchgate.net/publication/228798837_Neural_network_control_of_an_inverted_pendulum_on_a_cart" rel="nofollow noreferrer">solutions</a> have been implemented that balance the pendulum using Machine Learning frameworks instead of a pre-programmed algorithm.</p>
  <p>Unfortunately, the links listed are intended for people with some ML background, and could be completely opaque to a beginner, even a beginner with a programming background.</p>
  <p>Is there a complete set (&quot;stack&quot;) of software that is beginner-friendly with (relatively) detailed documentation that can be used for practical learning of ML-based motor/system control (i.e. learning through tinkering)?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-12-31T00:39:27.647Z
Comments.Text: Asking for software or tools is off-topic here. Having said that, I think you won't find things much easier than [gymnasium](https://gymnasium.farama.org/) (previously gym), which you can use to solve the inverted pendulum problem using reinforcement learning, which is the specific type of machine learning that is often applied to this problem. I'd recommend that you learn a bit about RL before getting into trying to solve problems with RL with tools, although you may also be able to actually play with the code examples, but you won't appreciate them fully without knowing the RL basics.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-12-31T00:43:07.130Z
Comments.Text: It would be like trying to use Django without knowing Python. You may be able to play with some code examples (especially if you have some programming or web development experience), but at some point you will need to learn Python properly. [The gynmsium docs](https://gymnasium.farama.org/) have a very brief intro to RL, but that's probably not enough if you want to learn things properly. For books on the topic, see https://ai.stackexchange.com/q/22010/2444
Comments.UserDisplayName: nbro
Tags: <control-problem><control-theory>
Title: Software stack for practical learning of an ML-based inverted pendulum system?
UserDisplayName: Noideas
ThreadText: # Software stack for practical learning of an ML-based inverted pendulum system?
  
  (Asked by: username_0 on 2024-12-29)
  
  Some background first: My programming background is Python and C. Also, "classical" control systems. I.e PID control, analogue, feedback-based correction etc.
  
  Inverted pendulum is a textbook control problem. Traditionally it is solved through use of some type of algorithm, most notably PID.
  
  Recently I've discovered that a [number](https://ai.stackexchange.com/questions/16812/can-supervised-learning-be-used-to-solve-the-inverted-pendulum-problem) of [successful](https://www.youtube.com/watch?v=5Q14EjnOJZc) [solutions](https://www.researchgate.net/publication/228798837_Neural_network_control_of_an_inverted_pendulum_on_a_cart) have been implemented that balance the pendulum using Machine Learning frameworks instead of a pre-programmed algorithm.
  
  Unfortunately, the links listed are intended for people with some ML background, and could be completely opaque to a beginner, even a beginner with a programming background.
  
  Is there a complete set ("stack") of software that is beginner-friendly with (relatively) detailed documentation that can be used for practical learning of ML-based motor/system control (i.e. learning through tinkering)?
  
  **Tags:** control-problem, control-theory
  
  > **Comments:**
  > **username_1**: Asking for software or tools is off-topic here. Having said that, I think you won't find things much easier than [gymnasium](https://gymnasium.farama.org/) (previously gym), which you can use to solve the inverted pendulum problem using reinforcement learning, which is the specific type of machine learning that is often applied to this problem. I'd recommend that you learn a bit about RL before getting into trying to solve problems with RL with tools, although you may also be able to actually play with the code examples, but you won't appreciate them fully without knowing the RL basics.  
  > **username_1**: It would be like trying to use Django without knowing Python. You may be able to play with some code examples (especially if you have some programming or web development experience), but at some point you will need to learn Python properly. [The gynmsium docs](https://gymnasium.farama.org/) have a very brief intro to RL, but that's probably not enough if you want to learn things properly. For books on the topic, see https://ai.stackexchange.com/q/22010/2444  
  
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  ## 0 answers
  
  