Machine Societies for Autonomous and Self-Governing Digital Ecosystems
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Updated time：2026-07-27 12:58:17 Views：6
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Abstract
Abstract---Bigger and more intricate digital ecosystems, from cloud resource markets to fleets of IoT devices, through electronic DeFi platforms, are increasingly demanding self-governance with minimal or no human oversight. This paper examines the concept of machine societies, constituted as a set of autonomous software agents which cooperate, negotiate and enforce policies in a decentralised way, and introduces a multi-layered architecture - named Machine Society Architecture (MSA) - consisting of autonomous agents, support with trust and reputation management, consensus based on blockchain technology, edge-cloud intelligence, and adaptive policy enforcement. Five original mathematical models were developed about the aspects of governance efficiency, reputation evolution, consensus latency, resilience, and multi objectives resource allocation. A series of five comparison tables and three experimental graphs are generated based on the simulated benchmark scenarios, comparing the proposed framework to existing centralized, DAO-based and federated multi-agent governance baselines in terms of ten metrics including governance efficiency, decision accuracy, consensus latency, communication overhead, resource utilization, scalability, trust score, resilience index, energy consumption and fault tolerance. The results demonstrate a steady increase in governance efficiency and trust, as well as other reduced latency and overheads, and improved resilience. It is concluded with some open challenges and future directions concerning trustworthy, scalable and self-governing machine societies.
Keywords
machine societies, autonomous digital ecosystems, decentralized governance, multi-agent collaboration, trust and reputation management, consensus mechanisms, blockchain-enabled coordination, edge-cloud intelligence, self-adaptive policy enforcement.
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