# Predator-prey survival pressure is sufficient to evolve swarming behaviors

arXiv: https://arxiv.org/abs/2308.12624 · HTML: https://mlsanity.com/paper/2308.12624/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Aug 2023.

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

- [Aquarium: A Comprehensive Framework for Exploring Predator-Prey Dynamics through Multi-Agent Reinforcement Learning Algorithms](https://mlsanity.com/paper/2401.07056/) (2024)
- [Evolutionary Dispersal of Ecological Species via Multi-Agent Deep Reinforcement Learning](https://mlsanity.com/paper/2410.18621/) (2024)
- [Unveiling Complex Collective Behaviors from Simple Rewards](https://mlsanity.com/paper/2607.12861/) (2026)

## Abstract (arXiv)

The comprehension of how local interactions arise in global collective behavior is of utmost importance in both biological and physical research. Traditional agent-based models often rely on static rules that fail to capture the dynamic strategies of the biological world. Reinforcement learning has been proposed as a solution, but most previous methods adopt handcrafted reward functions that implicitly or explicitly encourage the emergence of swarming behaviors. In this study, we propose a minimal predator-prey coevolution framework based on mixed cooperative-competitive multiagent reinforcement learning, and adopt a reward function that is solely based on the fundamental survival pressure, that is, prey receive a reward of -1 if caught by predators while predators receive a reward of +1. Surprisingly, our analysis of this approach reveals an unexpectedly rich diversity of emergent behaviors for both prey and predators, including flocking and swirling behaviors for prey, as well as dispersion tactics, confusion, and marginal predation phenomena for predators. Overall, our study provides novel insights into the collective behavior of organisms and highlights the potential applications in swarm robotics.