AAAI 2023technical6 citations
Embodied, Intelligent Communication for Multi-Agent Cooperation
Abstract
High-performing human teams leverage intelligent and efficient communication and coordination strategies to collaboratively maximize their joint utility. Inspired by teaming behaviors among humans, I seek to develop computational methods for synthesizing intelligent communication and coordination strategies for collaborative multi-robot systems. I leverage both classical model-based control and planning approaches as well as data-driven methods such as Multi-Agent Reinforcement Learning (MARL) to provide several contributions towards enabling emergent cooperative teaming behavior across both homogeneous and heterogeneous (including agents with different capabilities) robot teams.
BibTeX
@article{Seraj_2024, title={Embodied, Intelligent Communication for Multi-Agent Cooperation}, volume={37}, url={https://ojs.aaai.org/index.php/AAAI/article/view/26928}, DOI={10.1609/aaai.v37i13.26928}, abstractNote={High-performing human teams leverage intelligent and efficient communication and coordination strategies to collaboratively maximize their joint utility. Inspired by teaming behaviors among humans, I seek to develop computational methods for synthesizing intelligent communication and coordination strategies for collaborative multi-robot systems. I leverage both classical model-based control and planning approaches as well as data-driven methods such as Multi-Agent Reinforcement Learning (MARL) to provide several contributions towards enabling emergent cooperative teaming behavior across both homogeneous and heterogeneous (including agents with different capabilities) robot teams.}, number={13}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Seraj, Esmaeil}, year={2024}, month={Jul.}, pages={16135-16136} }