arXiv:2506.04236cs.MAcs.AI2025-06中稿 · ALIFE 2025被引 8

在区块链上让AI代理自主进化,探索持续创新的可能。

Spore in the Wild: A Case Study of Spore.fun as an Open-Environment Evolution Experiment with Sovereign AI Agents on TEE-Secured Blockchains

  • 用链上AI代理在开放环境运行,模拟生物演化。
  • 代理能自主控制社交账号与钱包,实现经济互动。
  • 适合关注AI自进化与去中心化系统的研究者。

在人工生命研究中,持续涌现新奇性的开放性演化(OEE)通常局限于封闭仿真系统,如Tierra和Avida,这些系统在初期创新后便陷入停滞。学者认为OEE需要能与环境持续交换信息或能量的开放系统。近期去中心化物理基础设施网络(DePIN)技术提供了无需许可的计算基础,使基于大语言模型的AI代理可在集成可信执行环境(TEEs)的区块链上运行,实现无须人工干预的自主性。这些代理可控制自身社交媒体账号与加密货币钱包,直接与区块链金融网络及人类社交平台交互。在此背景下,Spore.fun是一个真实的链上AI演化实验,支持代理的自主繁殖与演化。本文通过数字动物行为学方法,对Spore.fun中的代理行为与演化轨迹进行案例研究,旨在探讨基于无需许可计算资源与经济激励驱动的开放环境人工生命系统,是否可能最终实现长期追寻的OEE目标。

原文摘要 · Abstract (English)

In Artificial Life (ALife) research, replicating Open-Ended Evolution (OEE)-the continuous emergence of novelty observed in biological life-has usually been pursued within isolated, closed system simulations, such as Tierra and Avida, which have typically plateaued after an initial burst of novelty, failing to achieve sustained OEE. Scholars suggest that OEE requires an open-environment system that continually exchanges information or energy with its environment. A recent technological innovation in Decentralized Physical Infrastructure Network (DePIN), which provides permissionless computational substrates, enables the deployment of Large Language Model-based AI agents on blockchains integrated with Trusted Execution Environments (TEEs). This enables on-chain agents to operate autonomously "in the wild," achieving self-sovereignty without human oversight. These agents can control their own social media accounts and cryptocurrency wallets, allowing them to interact directly with blockchain-based financial networks and broader human social media. Building on this new paradigm of on-chain agents, Spore.fun is a recent real-world AI evolution experiment that enables autonomous breeding and evolution of new on-chain agents. This paper presents a detailed case study of Spore.fun, examining agent behaviors and their evolutionary trajectories through digital ethology. We aim to spark discussion about whether open-environment ALife systems "in the wild," based on permissionless computational substrates and driven by economic incentives to interact with their environment, could finally achieve the long-sought goal of OEE.

AI演化链上代理开放演化

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