1 citations · 1 across the 2 of their papers we have counts for
3 papers
Sampling-Based Coordination-Informed Multi-Objective Multi-Robot Reinforcement Learning
Antonio Marino, Esteban Restrepo, Soon-jo Chung +2
Multi-robot systems must simultaneously optimize competing objectives while maintaining coordinated behavior. Existing multi-agent reinforcement learning approaches often rely on f…
A Gated Graph Neural Network Approach to Fast-Convergent Dynamic Average Estimation
Antonio Marino, Claudio Pacchierotti, Paolo Robuffo Giordano
Dynamic average estimation is a critical problem in multi-agent systems, enabling agents to collaboratively estimate time-varying signals using only local information exchange. Tra…
Decentralized Reinforcement Learning for Multi-Agent Multi-Resource Allocation via Dynamic Cluster Agreements
Antonio Marino, Esteban Restrepo, Claudio Pacchierotti +1
This paper addresses the challenge of allocating heterogeneous resources among multiple agents in a decentralized manner. Our proposed method, Liquid-Graph-Time Clustering-IPPO, bu…