# Accelerate Reinforcement Learning with PID Controllers in the Pendulum Simulations

arXiv: https://arxiv.org/abs/2210.00770 · HTML: https://mlsanity.com/paper/2210.00770/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 16 of its 28 references that are in the map.
- First posted on arXiv 3 Oct 2022.

## Builds on (most cited first, 16 of 16)

- [OpenAI Gym](https://mlsanity.com/paper/1606.01540/) (2016)
- [QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation](https://mlsanity.com/paper/1806.10293/) (2018)
- [Learning Dexterous In-Hand Manipulation](https://mlsanity.com/paper/1808.00177/) (2018)
- [Deep Equilibrium Models](https://mlsanity.com/paper/1909.01377/) (2019)
- [Learning Quadrupedal Locomotion over Challenging Terrain](https://mlsanity.com/paper/2010.11251/) (2020)
- [Deep learning for universal linear embeddings of nonlinear dynamics](https://mlsanity.com/paper/1712.09707/) (2017)
- [Augmented Neural ODEs](https://mlsanity.com/paper/1904.01681/) (2019)
- [Learning Agile Robotic Locomotion Skills by Imitating Animals](https://mlsanity.com/paper/2004.00784/) (2020)
- [A Tour of Reinforcement Learning: The View from Continuous Control](https://mlsanity.com/paper/1806.09460/) (2018)
- [Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction](https://mlsanity.com/paper/2007.04439/) (2020)
- [Reinforcement Learning via Fenchel-Rockafellar Duality](https://mlsanity.com/paper/2001.01866/) (2020)
- [Deep Drone Acrobatics](https://mlsanity.com/paper/2006.05768/) (2020)
- [Actor-Critic Reinforcement Learning for Control with Stability Guarantee](https://mlsanity.com/paper/2004.14288/) (2020)
- [RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration](https://mlsanity.com/paper/1906.07372/) (2019)
- [Learning with Training Wheels: Speeding up Training with a Simple Controller for Deep Reinforcement Learning](https://mlsanity.com/paper/1812.05027/) (2018)
- [One-Shot High-Fidelity Imitation: Training Large-Scale Deep Nets with RL](https://mlsanity.com/paper/1810.05017/) (2018)

## Abstract (arXiv)

We propose a Proportional Integral Derivative (PID) controller-based coaching scheme to expedite reinforcement learning (RL).