# AI-Olympics: Exploring the Generalization of Agents through Open Competitions

arXiv: https://arxiv.org/abs/2405.14358 · HTML: https://mlsanity.com/paper/2405.14358/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 May 2024.

## Built on by (most cited first, 1 of 1)

- [Improving Sample Efficiency in Multi-Agent Reinforcement Learning for Simulated Football Games via Exploration](https://mlsanity.com/paper/2503.13077/) (2025)

## Abstract (arXiv)

Between 2021 and 2023, AI-Olympics, a series of online AI competitions was hosted by the online evaluation platform Jidi in collaboration with the IJCAI committee. In these competitions, an agent is required to accomplish diverse sports tasks in a two-dimensional continuous world, while competing against an opponent. This paper provides a brief overview of the competition series and highlights notable findings. We aim to contribute insights to the field of multi-agent decision-making and explore the generalization of agents through engineering efforts.