# COME TOGETHER: Multi-Agent Geometric Consensus (Gathering, Rendezvous, Clustering, Aggregation)

arXiv: https://arxiv.org/abs/1902.01455 · HTML: https://mlsanity.com/paper/1902.01455/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Feb 2019.

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

- [Task-Oriented Communication Design at Scale](https://mlsanity.com/paper/2305.08481/) (2023)
- [VariAntNet: Learning Decentralized Control of Multi-Agent Systems](https://mlsanity.com/paper/2509.02271/) (2025)
- [Sensor to Pixels: Decentralized Swarm Gathering via Image-Based Reinforcement Learning](https://mlsanity.com/paper/2601.03413/) (2026)

## Abstract (arXiv)

This report surveys results on distributed systems comprising mobile agents that are identical and anonymous, oblivious and interact solely by adjusting their motion according to the relative location of their neighbours. The agents are assumed capable of sensing the presence of other agents within a given sensing range and able to implement rules of motion based on full or partial information on the geometric constellation of their neighbouring agents. Eight different problems that cover assumptions of finite vs infinite sensing range, direction and distance vs direction only sensing and discrete vs continuous motion, are analyzed in the context of geometric consensus, clustering or gathering tasks.