ML//agent//multi-agent system

A multi-agent system contains multiple decision-making agents that can divide work, exchange observations or affect shared state. The agents may use identical models with different roles, different models, or simple deterministic workers beside model-driven planners.

A multi-agent system contains multiple decision-making agents that can divide work, exchange observations or affect shared state. The agents may use identical models with different roles, different models, or simple deterministic workers beside model-driven planners.

More agents do not automatically create more intelligence. They also introduce coordination cost, duplicated exploration, inconsistent beliefs and new failure modes around authority. Parallelism helps when work can be decomposed and results can be reconciled cheaply. Otherwise the system may merely manufacture a meeting.

The architecture matters more than the headcount.