# Fast and the Furious: Hot Starts in Pursuit-Evasion Games

arXiv: https://arxiv.org/abs/2510.10830 · HTML: https://mlsanity.com/paper/2510.10830/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 40 references that are in the map.
- First posted on arXiv 12 Oct 2025.

## Builds on (most cited first, 8 of 8)

- [Semi-Supervised Classification with Graph Convolutional Networks](https://mlsanity.com/paper/1609.02907/) (2016)
- [Emergence of Grounded Compositional Language in Multi-Agent Populations](https://mlsanity.com/paper/1703.04908/) (2017)
- [pymoo: Multi-objective Optimization in Python](https://mlsanity.com/paper/2002.04504/) (2020)
- [TacticAI: an AI assistant for football tactics](https://mlsanity.com/paper/2310.10553/) (2023)
- [Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations](https://mlsanity.com/paper/1903.06669/) (2019)
- [An Introduction to Pursuit-evasion Differential Games](https://mlsanity.com/paper/2003.05013/) (2020)
- [Grasper: A Generalist Pursuer for Pursuit-Evasion Problems](https://mlsanity.com/paper/2404.12626/) (2024)
- [Pursuer Assignment and Control Strategies in Multi-agent Pursuit-Evasion Under Uncertainties](https://mlsanity.com/paper/2103.15660/) (2021)

## Abstract (arXiv)

Effectively positioning pursuers in pursuit-evasion games without prior knowledge of evader locations remains a significant challenge. A novel approach that combines game-theoretic control theory with Graph Neural Networks is introduced in this work. By conceptualizing pursuer configurations as strategic arrangements and representing them as graphs, a Graph Characteristic Space is constructed via multi-objective optimization to identify Pareto-optimal configurations. A Graph Convolutional Network (GCN) is trained on these Pareto-optimal graphs to generate strategically effective initial configurations, termed "hot starts". Empirical evaluations demonstrate that the GCN-generated hot starts provide a significant advantage over random configurations. In scenarios considering multiple pursuers and evaders, this method hastens the decline in evader survival rates, reduces pursuer travel distances, and enhances containment, showcasing clear strategic benefits.