Intelligent System of Emergent Knowledge: A Coordination Fabric for Billions of Minds
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Abstract (arXiv)
The Intelligent System of Emergent Knowledge (ISEK) establishes a decentralized network where human and artificial intelligence agents collaborate as peers, forming a self-organizing cognitive ecosystem. Built on Web3 infrastructure, ISEK combines three fundamental principles: (1) a decentralized multi-agent architecture resistant to censorship, (2) symbiotic AI-human collaboration with equal participation rights, and (3) resilient self-adaptation through distributed consensus mechanisms. The system implements an innovative coordination protocol featuring a six-phase workflow (Publish, Discover, Recruit, Execute, Settle, Feedback) for dynamic task allocation, supported by robust fault tolerance and a multidimensional reputation system. Economic incentives are governed by the native ISEK token, facilitating micropayments, governance participation, and reputation tracking, while agent sovereignty is maintained through NFT-based identity management. This synthesis of blockchain technology, artificial intelligence, and incentive engineering creates an infrastructure that actively facilitates emergent intelligence. ISEK represents a paradigm shift from conventional platforms, enabling the organic development of large-scale, decentralized cognitive systems where autonomous agents collectively evolve beyond centralized constraints.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 21 references that are in the map. First posted on arXiv 11 Jun 2025.
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References · 17
- 2025AgentNet: Decentralized Evolutionary Coordination for LLM-based Multi-Agent Systemscited by 90
- 2025A Survey of AI Agent Protocolscited by 81
- 2025Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agentscited by 71
- 2025Multi-Agent Coordination across Diverse Applications: A Surveycited by 37
- 2023Wireless Multi-Agent Generative AI: From Connected Intelligence to Collective Intelligencecited by 26
- 2025Advancing Multi-Agent Systems Through Model Context Protocol: Architecture, Implementation, and Applicationscited by 23
- 2025Human-Artificial Interaction in the Age of Agentic AI: A System-Theoretical Approachcited by 22
- 2023Context-aware Communication for Multi-agent Reinforcement Learningcited by 13
- 2025Trustless Autonomy: Understanding Motivations, Benefits, and Governance Dilemmas in Self-Sovereign Decentralized AI Agentscited by 10
- 2025SRMT: Shared Memory for Multi-agent Lifelong Pathfindingcited by 8
- 2024Beyond the Sum: Unlocking AI Agents Potential Through Market Forcescited by 4
- 2025The Society of HiveMind: Multi-Agent Optimization of Foundation Model Swarms to Unlock the Potential of Collective Intelligencecited by 4
5 more
- 2024Decentralized Intelligence Network (DIN)cited by 2
- 2024Incentivized Symbiosis: A Paradigm for Human-Agent Coevolutioncited by 2
- 2025Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordinationcited by 2
- 2025On the Day They Experience: Awakening Self-Sovereign Experiential AI Agentscited by 2
- 2025A hybrid marketplace of ideascited by 1
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