# MOBA: a New Arena for Game AI

arXiv: https://arxiv.org/abs/1705.10443 · HTML: https://mlsanity.com/paper/1705.10443/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 May 2017.

## Built on by (most cited first, 5 of 5)

- [Learning Diverse Policies in MOBA Games via Macro-Goals](https://mlsanity.com/paper/2110.14221/) (2021)
- [Towards Effective and Interpretable Human-Agent Collaboration in MOBA Games: A Communication Perspective](https://mlsanity.com/paper/2304.11632/) (2023)
- [Enhancing Human Experience in Human-Agent Collaboration: A Human-Centered Modeling Approach Based on Positive Human Gain](https://mlsanity.com/paper/2401.16444/) (2024)
- [The Dota 2 Bot Competition](https://mlsanity.com/paper/2103.02943/) (2021)
- [Reinforcement Learning for Adaptive Video Compressive Sensing](https://mlsanity.com/paper/2105.08205/) (2021)

## Abstract (arXiv)

Games have always been popular testbeds for Artificial Intelligence (AI). In the last decade, we have seen the rise of the Multiple Online Battle Arena (MOBA) games, which are the most played games nowadays. In spite of this, there are few works that explore MOBA as a testbed for AI Research. In this paper we present and discuss the main features and opportunities offered by MOBA games to Game AI Research. We describe the various challenges faced along the game and also propose a discrete model that can be used to better understand and explore the game. With this, we aim to encourage the use of MOBA as a novel research platform for Game AI.