Heterogeneous Team

Heterogeneous teams, composed of agents with diverse capabilities and roles, are a burgeoning research area aiming to optimize collaboration and performance in complex tasks. Current research focuses on developing algorithms and models, such as hierarchical reinforcement learning, multi-agent multi-armed bandits, and large language models, to effectively manage task allocation, communication, and coordination within these teams, often addressing challenges like information uncertainty and ad hoc collaboration. This work holds significant implications for improving efficiency and robustness in various domains, including multi-robot systems, human-AI collaboration, and even organizational team dynamics, by providing frameworks for leveraging the strengths of diverse agents.