# Combat Models for RTS Games

arXiv: https://arxiv.org/abs/1605.05305 · HTML: https://mlsanity.com/paper/1605.05305/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 May 2016.

## Built on by (most cited first, 3 of 3)

- [SC2EGSet: StarCraft II Esport Replay and Game-state Dataset](https://mlsanity.com/paper/2207.03428/) (2022)
- [Turing Completeness and Sid Meier's Civilization](https://mlsanity.com/paper/2104.14647/) (2021)
- [SAT-RTS: A systematic framework for tactical knowledge extraction and visualization-based analysis in real-time strategy games](https://mlsanity.com/paper/2606.30090/) (2026)

## Abstract (arXiv)

Game tree search algorithms, such as Monte Carlo Tree Search (MCTS), require access to a forward model (or "simulator") of the game at hand. However, in some games such forward model is not readily available. This paper presents three forward models for two-player attrition games, which we call "combat models", and show how they can be used to simulate combat in RTS games. We also show how these combat models can be learned from replay data. We use StarCraft as our application domain. We report experiments comparing our combat models predicting a combat output and their impact when used for tactical decisions during a real game.