16 citations · 39 across the 11 of their papers we have counts for
4 papers · 1 filter
When Is Diversity Rewarded in Cooperative Multi-Agent Learning?
Michael Amir, Matteo Bettini, Amanda Prorok
The success of teams in robotics, nature, and society often depends on the division of labor among diverse specialists; however, a principled explanation for when such diversity su…
Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning
Matteo Bettini, Ryan Kortvelesy, Amanda Prorok
The study of behavioral diversity in Multi-Agent Reinforcement Learning (MARL) is a nascent yet promising field. In this context, the present work deals with the question of how to…
System Neural Diversity: Measuring Behavioral Heterogeneity in Multi-Agent Learning
Matteo Bettini, Ajay Shankar, Amanda Prorok
Evolutionary science provides evidence that diversity confers resilience in natural systems. Yet, traditional multi-agent reinforcement learning techniques commonly enforce homogen…
On the properties of path additions for traffic routing
Matteo Bettini, Amanda Prorok
In this paper we investigate the impact of path additions to transport networks with optimised traffic routing. In particular, we study the behaviour of total travel time, and cons…