Embodied, Intelligent Communication for Multi-Agent Cooperation
نویسندگان
چکیده
High-performing human teams leverage intelligent and efficient communication coordination strategies to collaboratively maximize their joint utility. Inspired by teaming behaviors among humans, I seek develop computational methods for synthesizing collaborative multi-robot systems. both classical model-based control planning approaches as well data-driven such Multi-Agent Reinforcement Learning (MARL) provide several contributions towards enabling emergent cooperative behavior across homogeneous heterogeneous (including agents with different capabilities) robot teams.
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ژورنال
عنوان ژورنال: Proceedings of the ... AAAI Conference on Artificial Intelligence
سال: 2023
ISSN: ['2159-5399', '2374-3468']
DOI: https://doi.org/10.1609/aaai.v37i13.26928