Decentralized Agent

Decentralized agents represent a growing area of research focusing on enabling multiple autonomous entities to collaboratively achieve goals without relying on a central controller. Current research emphasizes developing algorithms and architectures, such as multi-agent reinforcement learning (MARL) with various communication strategies (e.g., localized, networked), and model-based approaches, to improve coordination, efficiency, and robustness in diverse applications. This field is significant because it addresses scalability and security limitations of centralized systems, offering solutions for complex problems in areas like traffic control, cloud computing, and multi-robot coordination.