How do centralized and decentralized architectures differ in AI agents?

Centralized architectures rely on a single controlling agent or a small number of agents responsible for making decisions and managing resources. In contrast, decentralized architectures distribute decision-making across multiple agents, each capable of acting autonomously. This leads to enhanced scalability and resilience in decentralized systems, as agents can continue to operate independently even if some fail or disconnect. However, centralized systems can offer more straightforward coordination and control, potentially leading to more efficient decision-making in specific contexts.