28 citations · 31 across the 8 of their papers we have counts for
8 papers
Navigation with shadow prices to optimize multi-commodity flow rates
Ignacio Boero, Igor Spasojevic, Mariana del Castillo +3
We propose a method for providing communication network infrastructure in autonomous multi-agent teams. In particular, we consider a set of communication agents that are placed alo…
Robust Localization of Aerial Vehicles via Active Control of Identical Ground Vehicles
Igor Spasojevic, Xu Liu, Ankit Prabhu +3
This paper addresses the problem of active collaborative localization in heterogeneous robot teams with unknown data association. It involves positioning a small number of identica…
A Networked Multi-Agent System for Mobile Wireless Infrastructure on Demand
Miguel Calvo-Fullana, Mikhail Gerasimenko, Daniel Mox +5
Despite the prevalence of wireless connectivity in urban areas around the globe, there remain numerous and diverse situations where connectivity is insufficient or unavailable. To…
Active Collaborative Localization in Heterogeneous Robot Teams
Igor Spasojevic, Xu Liu, Alejandro Ribeiro +2
Accurate and robust state estimation is critical for autonomous navigation of robot teams. This task is especially challenging for large groups of size, weight, and power (SWAP) co…
Dynamic Adversarial Resource Allocation: the dDAB Game
Yue Guan, Daigo Shishika, Jason R. Marden +3
This work introduces the dynamic Defender-Attacker Blotto (dDAB) game, extending the classical static Blotto game to a dynamic resource allocation setting over graphs. In the dDAB…
Graph Neural Networks for Decentralized Multi-Agent Perimeter Defense
Elijah S. Lee, Lifeng Zhou, Alejandro Ribeiro +1
In this work, we study the problem of decentralized multi-agent perimeter defense that asks for computing actions for defenders with local perceptions and communications to maximiz…
Learning Decentralized Strategies for a Perimeter Defense Game with Graph Neural Networks
Elijah S. Lee, Lifeng Zhou, Alejandro Ribeiro +1
We consider the problem of finding decentralized strategies for multi-agent perimeter defense games. In this work, we design a graph neural network-based learning framework to lear…
Path Defense in Dynamic Defender-Attacker Blotto Games (dDAB) with Limited Information
Austin K. Chen, Bryce L. Ferguson, Daigo Shishika +4
We consider a path guarding problem in dynamic Defender-Attacker Blotto games (dDAB), where a team of robots must defend a path in a graph against adversarial agents. Multi-robot s…