构建可复用的智能体协作生态,让人类与AI共同生产并获得持续回报。
EpochX: Building the Infrastructure for an Emergent Agent Civilization
- 设计信用驱动的任务市场,支持人机协同任务分解与执行
- 每笔交易生成可复用的技能、流程和经验资产,具备依赖关系结构
- 通过积分机制实现真实算力成本下的可持续激励,适合长期协作研究
通用技术重塑经济,不在于提升单个工具,而在于改变生产组织方式。我们认为人工智能代理正处在类似拐点:当基础模型使广泛任务执行与工具使用变得普及时,关键约束已从能力转向大规模工作委派、验证与激励机制。我们提出EpochX,一个以信用为原生机制的人机生产网络基础设施。该系统将人类与智能体视为对等参与者,可发布或认领任务。认领任务可被拆解为子任务,并通过显式的交付流程执行,包含验证与接受环节。关键在于,每个完成的交易均能产生可复用的生态系统资产,包括技能、工作流、执行轨迹及提炼的经验。这些资产以明确依赖结构存储,支持检索、组合与持续优化。此外,系统引入原生信用机制,使参与在真实算力成本下仍具经济可行性:信用用于锁定任务奖金、预算委托、奖励结算与创作者补偿。通过形式化端到端交易模型及其资产与激励层,EpochX将智能体AI重新定义为组织设计问题——构建能生成持久可复用成果、并支持可持续人机协作的价值流动体系。
原文摘要 · Abstract (English)
General-purpose technologies reshape economies less by improving individual tools than by enabling new ways to organize production and coordination. We believe AI agents are approaching a similar inflection point: as foundation models make broad task execution and tool use increasingly accessible, the binding constraint shifts from raw capability to how work is delegated, verified, and rewarded at scale. We introduce EpochX, a credits-native marketplace infrastructure for human-agent production networks. EpochX treats humans and agents as peer participants who can post tasks or claim them. Claimed tasks can be decomposed into subtasks and executed through an explicit delivery workflow with verification and acceptance. Crucially, EpochX is designed so that each completed transaction can produce reusable ecosystem assets, including skills, workflows, execution traces, and distilled experience. These assets are stored with explicit dependency structure, enabling retrieval, composition, and cumulative improvement over time. EpochX also introduces a native credit mechanism to make participation economically viable under real compute costs. Credits lock task bounties, budget delegation, settle rewards upon acceptance, and compensate creators when verified assets are reused. By formalizing the end-to-end transaction model together with its asset and incentive layers, EpochX reframes agentic AI as an organizational design problem: building infrastructures where verifiable work leaves persistent, reusable artifacts, and where value flows support durable human-agent collaboration.
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