hive-mind-advanced

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Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory

AI & Automation 57,130 stars 6508 forks Updated today MIT

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Skill Content

# Hive Mind Advanced Skill Master the advanced Hive Mind collective intelligence system for sophisticated multi-agent coordination using queen-led architecture, Byzantine consensus, and collective memory. ## Overview The Hive Mind system represents the pinnacle of multi-agent coordination in Claude Flow, implementing a queen-led hierarchical architecture where a strategic queen coordinator directs specialized worker agents through collective decision-making and shared memory. ## Core Concepts ### Architecture Patterns **Queen-Led Coordination** - Strategic queen agents orchestrate high-level objectives - Tactical queens manage mid-level execution - Adaptive queens dynamically adjust strategies based on performance **Worker Specialization** - Researcher agents: Analysis and investigation - Coder agents: Implementation and development - Analyst agents: Data processing and metrics - Tester agents: Quality assurance and validation - Architect agents: System design and planning - Reviewer agents: Code review and improvement - Optimizer agents: Performance enhancement - Documenter agents: Documentation generation **Collective Memory System** - Shared knowledge base across all agents - LRU cache with memory pressure handling - SQLite persistence with WAL mode - Memory consolidation and association - Access pattern tracking and optimization ### Consensus Mechanisms **Majority Consensus** Simple voting where the option with most votes wins. **Weighted Consensus** Queen vote...

Details

Author
ruvnet
Repository
ruvnet/ruflo
Created
12 months ago
Last Updated
today
Language
TypeScript
License
MIT

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