hive-mind-advanced

Multi-agent coordination is achieved through a queen-led hierarchical architecture where strategic queens define plans, tactical queens manage sprints, and specialized worker agents execute specific modules using collective memory for shared learning.

Byzantine fault tolerance in swarm systems ensures reliable collective decision-making even when individual agents fail or act maliciously, using consensus mechanisms to maintain system integrity across the multi-agent coordination network.

Initialize the multi-agent system by running the command `npx claude-flow hive-mind init` to establish the swarm coordination environment, which automatically configures persistent collective memory for knowledge sharing across agents.

Worker agent specialization is fully supported, allowing you to assign diverse roles such as researcher, coder, and analyst to individual agents for efficient task execution within the hierarchical swarm coordination architecture.

Consensus management is handled through configurable mechanisms including majority voting, weighted voting, and Byzantine fault-tolerant consensus, ensuring reliable decision-making tailored to your multi-agent system's specific requirements.

The swarm coordination system operates with zero external dependencies, running entirely self-contained to orchestrate queen-led hierarchies, worker specializations, and collective memory without requiring additional packages or components.