Reinforcement Learning for Athletic Intelligence: Lessons from the 1st "AI Olympics with RealAIGym" Competition
Editors: Kate Larson
In Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI-24, (IJCAI-2024), 03.8.-09.8.2024, Jeju, International Joint Conferences on Artificial Intelligence Organization, pages 8833-8837, Aug/2024.
Abstract :
As artifcial intelligence gains new capabilities, itbecomes important to evaluate it on real-world tasks. In particular, the felds of robotics and reinforcement learning (RL) are lacking in standardized benchmarking tasks on real hardware. To facilitate reproducibility and stimulate algorithmic advancements, we held an AI Olympics competition at IJCAI 2023 conference based on the double pendulum system in the RealAIGym project where the participants were asked to develop a controller for the swing up and stabilization task. This paper presents the methods and results from the top participating teams and provides insights into the realworld performance of RL algorithms with respectto a baseline time-varying LQR controller.Files:
20241001_Reinforcement_Learning_for_Athletic_Intelligence.pdfLinks:
https://doi.org/10.24963/ijcai.2024/1043https://www.ijcai.org/proceedings/2024/1043