# Using reinforcement learning to design an AI assistantfor a satisfying co-op experience

arXiv: https://arxiv.org/abs/2105.03414 · HTML: https://mlsanity.com/paper/2105.03414/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 5 references that are in the map.
- First posted on arXiv 7 May 2021.

## Builds on (most cited first, 2 of 2)

- [Asynchronous Methods for Deep Reinforcement Learning](https://mlsanity.com/paper/1602.01783/) (2016)
- [CraftAssist: A Framework for Dialogue-enabled Interactive Agents](https://mlsanity.com/paper/1907.08584/) (2019)

## Abstract (arXiv)

In this project, we designed an intelligent assistant player for the single-player game Space Invaders with the aim to provide a satisfying co-op experience. The agent behaviour was designed using reinforcement learning techniques and evaluated based on several criteria. We validate the hypothesis that an AI-driven computer player can provide a satisfying co-op experience.