@conference {1502899,
	title = {A Detailed Analysis of a Multi-agent Diverse Team },
	booktitle = {Coordination, Organizations, Institutions and Norms in Agent Systems IX. Springer-Verlag Lecture Notes in AI},
	year = {2014},
	abstract = { In an open system we can have many different kinds of agents. However, it is a challenge to decide which agents to pick when forming multi-agent
teams. 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.},
	author = {Marcolino, Leandro Soriano and Zhang, Chao and Xin Jiang, Albert and Tambe, Milind},
	editor = {T. Balke and A. Chopra and F. Dignum and B. van Riemsdijk}
}
