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Agentic Hives framework models self-organizing multi-agent systems dynamics

Researchers have introduced the Agentic Hive, a novel framework for managing self-organizing multi-agent AI systems with dynamic populations. This system allows agents to be created, destroyed, or re-specialized in real-time, adapting to changing resources and objectives. The framework, drawing on economic growth theory, proves the existence of a Pareto optimal equilibrium and identifies conditions for multiple equilibria, endogenous cycles, and instability. AI

IMPACT Provides a formal toolkit for operators to predict and steer the demographic evolution of self-organizing multi-agent systems.

RANK_REASON This is a research paper introducing a new theoretical framework for multi-agent systems.

Read on arXiv cs.AI →

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Agentic Hives framework models self-organizing multi-agent systems dynamics

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This is a research paper introducing a new theoretical framework for multi-agent systems.
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Jean-Philippe Garnier (Br.AI.K) ·

    Agentic Hives: Equilibrium, Indeterminacy, and Endogenous Cycles in Self-Organizing Multi-Agent Systems

    arXiv:2603.00130v2 Announce Type: replace-cross Abstract: Current multi-agent AI systems operate with a fixed number of agents whose roles are specified at design time. No formal theory governs when agents should be created, destroyed, or re-specialized at runtime-let alone how t…