# General Video Game AI: Learning from Screen Capture

arXiv: https://arxiv.org/abs/1704.06945 · HTML: https://mlsanity.com/paper/1704.06945/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Apr 2017.

## Built on by (most cited first, 2 of 2)

- [Handcrafted Feature Selection Techniques for Pattern Recognition: A Survey](https://mlsanity.com/paper/2209.02746/) (2022)
- [Learning to Play: Reinforcement Learning and Games](https://mlsanity.com/paper/2610.17391/) (2026)

## Abstract (arXiv)

General Video Game Artificial Intelligence is a general game playing framework for Artificial General Intelligence research in the video-games domain. In this paper, we propose for the first time a screen capture learning agent for General Video Game AI framework. A Deep Q-Network algorithm was applied and improved to develop an agent capable of learning to play different games in the framework. After testing this algorithm using various games of different categories and difficulty levels, the results suggest that our proposed screen capture learning agent has the potential to learn many different games using only a single learning algorithm.