Multi-Agent Systems

MUL-tee AY-juhnt SIS-tuhmz /ˌmʌlti ˈeɪdʒənt ˈsɪstəmz/

Systems where multiple AI “agents” work together, each with a role such as planning, researching, checking or executing steps. Agents can collaborate or compete to solve complex tasks. Multi-agent approaches can improve coverage and reliability, but they can also multiply errors if agents share the same wrong assumptions or unreliable sources.