---
title: "Multi-Agent Team Formation: Diversity Beats Strength?"
authors:
  - "Leandro Soriano Marcolino"
  - "Albert Xin Jiang"
  - "Milind Tambe"
doi: ""
url: "https://ijcai.org/proceedings/2013/50"
pdf: "https://ijcai.org/proceedings/2013/0050.pdf"
venue: "Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence"
year: 2013
pages: "279-284"
track: ""
keywords:
---

# Multi-Agent Team Formation: Diversity Beats Strength?

Leandro Soriano Marcolino, Albert Xin Jiang, Milind Tambe

*Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence*, pages 279-284.

## Abstract

Team formation is a critical step in deploying a multi-agent team. In some scenarios, agents coordinate by voting continuously. When forming such teams, should we focus on the diversity of the team or on the strength of each member? Can a team of diverse (and weak) agents outperform a uniform team of strong agents? We propose a new model to address these questions. Our key contributions include: (i) we show that a diverse team can overcome a uniform team and we give the necessary conditions for it to happen; (ii) we present optimal voting rules for a diverse team; (iii) we perform synthetic experiments that demonstrate that both diversity and strength contribute to the performance of a team; (iv) we show experiments that demonstrate the usefulness of our model in one of the most difficult challenges for Artificial Intelligence: Computer Go.