# Augmenting Automated Game Testing with Deep Reinforcement Learning

*Source* · `src-bergdahl-2020-augmenting-automated-testing-drl` · status: **n/a**

| field | value |
|---|---|
| kind | Peer-reviewed paper |
| authors | Joakim Bergdahl, Camilo Gordillo, Konrad Tollmar, Linus Gisslén |
| venue | IEEE Conference on Games 2020 |
| date | 2020-08 |
| arxiv | 2103.15819 |
| accessed | 2026-10-24 |

## Notes

EA SEED; four sandbox environments; an RL agent found a wall missing its collision mesh that scripted navmesh agents missed, and timeouts located all five stuck areas.

## Backlinks (computed)

**cited by:** [Agent-based automated playtesting and balancing](../technique/automated-playtesting.md)

## Citation

Joakim Bergdahl, Camilo Gordillo, Konrad Tollmar, Linus Gisslén (2020-08). *Augmenting Automated Game Testing with Deep Reinforcement Learning*. IEEE Conference on Games 2020 https://arxiv.org/abs/2103.15819

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Provenance: created in run `2026-10-24-techniques-rl-design`.