# Winning Isn't Everything: Enhancing Game Development with Intelligent Agents

*Source* · `src-zhao-2019-winning-isnt-everything` · status: **n/a**

| field | value |
|---|---|
| kind | Preprint |
| venue | arXiv |
| date | 2019-03-25 |
| arxiv | 1903.10545 |
| accessed | 2026-10-24 |

## Authors

- Yunqi Zhao
- Igor Borovikov
- Fernando de Mesentier Silva
- Ahmad Beirami
- Jason Rupert
- Caedmon Somers
- Jesse Harder
- John Kolen
- Jervis Pinto
- Reza Pourabolghasem
- James Pestrak
- Harold Chaput
- Mohsen Sardari
- Long Lin
- Sundeep Narravula
- Navid Aghdaie
- Kazi Zaman

## Notes

Electronic Arts; case studies include The Sims Mobile career balancing with A* and evolution strategies; deep RL needed heavy tuning per target game, so effort scaled roughly linearly with the number of games.

## Backlinks (computed)

**cited by:** [Agent-based automated playtesting and balancing](../technique/automated-playtesting.md), [Deep reinforcement learning policies for NPC opponents and navigation](../technique/deep-rl-npc-policies.md)

## Citation

Yunqi Zhao, Igor Borovikov, Fernando de Mesentier Silva, Ahmad Beirami, Jason Rupert, Caedmon Somers, Jesse Harder, John Kolen, Jervis Pinto, Reza Pourabolghasem, James Pestrak, Harold Chaput, Mohsen Sardari, Long Lin, Sundeep Narravula, Navid Aghdaie, Kazi Zaman (2019-03-25). *Winning Isn't Everything: Enhancing Game Development with Intelligent Agents*. arXiv https://arxiv.org/abs/1903.10545

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