hive-mind-advanced

You coordinate multi-agent systems using a queen-led architecture with consensus and persistent memory. This enables complex, structured decision-making across specialized agents like researchers, coders, analysts, and testers working in concert.

Queen-led orchestration provides strategic planning and directive task distribution across specialized worker agents. The queen coordinates researchers, architects, and reviewers to execute large-scale simulations and distributed planning tasks.

Start a swarm session by initializing the hive, spawning a queen and specialized workers, and issuing an initial objective. The system manages task distribution, collective memory, and consensus mechanisms.

Yes, the multi-agent coordination system supports Byzantine fault-tolerant consensus mechanisms. It includes majority, weighted, and Byzantine approval strategies for robust distributed decision-making across specialized roles.

Yes, you can use collective memory and checkpointing for long-running experiments. The system provides shared knowledge stores, context management, search, and association features for session traceability and persistence.

Worker specialization is limited to predefined roles such as researchers, coders, analysts, testers, architects, reviewers, optimizers, and documenters. The architecture relies on queen-led coordination for task distribution across these specific functions.