Multi-Agent Systems

Autonomous AI teams (agents) that collaborate, coordinate, or compete to solve complex, large-scale problems; think distributed intelligence for maximum resilience and efficiency.

Multi-Agent Systems (MAS) are computational architectures comprising multiple autonomous, interacting agents (software, LLMs, or robots) that distribute tasks to achieve a collective goal. This decentralized model is critical for tackling challenges too complex for a single AI: for example, a self-driving system uses separate agents for obstacle detection, mapping, and real-time decision-making. The core advantage is superior resilience and scalability; if one agent fails, the system maintains operations. MAS is actively deployed across logistics, finance, and healthcare, leveraging parallel execution to enhance decision-making and streamline complex workflows like supply chain negotiation.

https://cloud.google.com/learn/what-is-multi-agent-system-in-ai