深度分析 @TheoriqAI ：专注于多智能体系统（MAS, Multi-Agent Systems）与 AI 推理（AI reasoning）的加密项目，旨在打造智能代理（Agentic AI）驱动的去中心化网络层，其愿景是在区块链和 Web3 世界中构建一个由 AI 代理自主交互、协作和进化的系统。 核心技术逻辑与产品进展 1、多智能体系统（Multi-Agent System）架构 Theoriq 构建一个环境，使得多个 AI 智能体（Agents）能够： • 相互通信（peer-to-peer message passing） • 协同完成任务（collaborative reasoning） • 以去中心化方式运行和进化（无需中心控制） 每个 Agent 既可以代表一个人类用户的意图，也可以是一个 DAO 的子模块，拥有自主决策能力。 2. 基于知识图谱和符号推理的 AI 模型 • 与传统 LLM 不同， @TheoriqAI 强调 结构化知识表达与逻辑推理能力。 • 使用“逻辑型 AI（Neuro-symbolic AI）” 结合 神经网络 + 规则系统。 • Agents 之间的互动遵循一种可验证的逻辑系统，保证“对话的因果性”和“协作的可解释性”。 3. Crypto-Native 机制设计 • 智能体行为通过区块链记录，可审计、可激励、可组合。 • 使用 token 机制激励 Agent 创建者、维护者和开发者。 • 支持 Agent-as-a-Service（AaaS）经济模型，即用户可以租用、交易智能体的服务。 4.首个应用：OLP 代理群： @TheoriqAI 近期推出了 Onchain Liquidity Provisioning（OLP）Swarm，专注于解决去中心化金融（DeFi）和传统金融中的流动性管理问题。该系统通过 Observer Agent收集链上数据，结合策略和流动性供应代理，动态调整流动性池配置以应对市场波动，实现从数据收集到策略执行的全自动化。 5.测试网进展： 2024 年底， @TheoriqAI 推出激励性测试网，吸引了大量用户与 AI 代理互动，短短几周内交互次数超过 2,000 万次，平均每天 60 万次。测试网采用 Proof of Engagement机制，用户通过社交任务、每日交互、反馈和推荐等方式赚取 XP 积分，积分将延续到未来阶段，并可能与代币空投相关 竞争优势 1、 @TheoriqAI 的 AI 代理基础层采用模块化设计，代理间具有高度的 互操作性（Interoperability）和 可组合性（Composability）。不同代理可以无缝协作，将专业能力整合成更强大的系统，例如市场分析代理与交易执行代理配合完成复杂金融策略。这种设计使其区别于传统集中式 AI 系统，提供了更高的灵活性和创新空间。 2、 @TheoriqAI 推出 Infinity Hub，作为一个去中心化的 AI 代理和资源市场，允许开发者发布代理，用户根据评级和评论选择合适的代理。这种市场机制类似于全球化的专业化贸易，促进了代理协作和任务效率的提升 3、通过与 http://io.net 和 0G Labs 的合作， @TheoriqAI 利用去中心化的 GPU 集群和无限扩展的存储能力，显著降低了计算和存储成本，同时提高了实时处理能力 4、 @TheoriqAI 优先聚焦于 DeFi 和游戏领域，通过 OLP Swarm 和与 Play AI 的合作，针对特定行业痛点（如流动性管理和玩家体验）提供定制化解决方案 总结 @TheoriqAI 的核心竞争力在于： • 构建 AI 代理的逻辑自治系统； • 专注于知识与推理（而非仅依赖 LLM）； • 推动 Web3 世界进入“多智能体协同智能阶段”。 这使它在“Agentic AI + Crypto” 的交叉赛道中拥有较强的差异化定位。未来一旦推出开发工具或 SDK，有潜力成为下一代去中心化 AI 协作平台的基础设施。 In-depth Analysis of @TheoriqAI: A crypto project focused on Multi-Agent Systems (MAS) and AI reasoning, Theoriq aims to build a decentralized network layer powered by Agentic AI. Its vision is to create a system in the blockchain and Web3 world where AI agents autonomously interact, collaborate, and evolve. Core Technical Logic and Product Progress 1. Multi-Agent System Architecture Theoriq creates an environment where multiple AI agents can: • Communicate via peer-to-peer message passing • Collaboratively perform reasoning tasks • Operate and evolve in a decentralized manner without central control Each agent can represent a human user’s intent or act as a DAO module with autonomous decision-making capabilities. 2. AI Model Based on Knowledge Graphs and Symbolic Reasoning • Unlike traditional LLMs, @TheoriqAI emphasizes structured knowledge representation and logical reasoning. • Employs neuro-symbolic AI, combining neural networks with rule-based systems. • Agent interactions follow a verifiable logic system to ensure causality in dialogue and explainability in collaboration. 3. Crypto-Native Mechanism Design • Agent behaviors are recorded on-chain, enabling auditability, incentives, and composability. • Token mechanisms incentivize agent creators, maintainers, and developers. • Supports Agent-as-a-Service (AaaS) model—users can rent or trade agent services. 4.First Application: OLP Swarm @TheoriqAI recently launched the Onchain Liquidity Provisioning (OLP) Swarm, addressing liquidity management in DeFi and traditional finance. It includes Observer Agents to collect on-chain data and pairs them with strategy and liquidity provisioning agents to dynamically manage liquidity pool allocations and adapt to market volatility—automating the full cycle from data collection to strategy execution. 5.Testnet Progress By the end of 2024, @TheoriqAI launched an incentivized testnet, attracting significant user interaction. In just a few weeks, over 20 million interactions occurred, averaging 600,000 per day. The testnet uses a Proof of Engagement model where users earn XP through social tasks, daily interactions, feedback, and referrals. XP may be tied to future token airdrops. Competitive Advantages 1. Modular Agent Architecture Agents have high interoperability and composability, enabling seamless collaboration. For example, a market analysis agent can pair with a trading execution agent to perform complex strategies. This sets Theoriq apart from centralized AI systems by offering more flexibility and innovation space. 2. Infinity Hub A decentralized marketplace for AI agents and resources where developers can publish agents and users can choose based on reviews and ratings. This marketplace promotes efficient agent collaboration and specialized global-scale operations. 3. Infrastructure Partnerships By collaborating with http://io.net and 0G Labs, @TheoriqAI utilizes decentralized GPU clusters and infinitely scalable storage, reducing cost while enhancing real-time processing capability. 4. Vertical Focus on DeFi and Gaming Through the OLP Swarm and collaboration with Play AI, Theoriq delivers customized solutions addressing specific industry pain points such as liquidity management and player experience. Summary @TheoriqAI core competitive strengths: • Logical autonomy system for AI agents • Focus on structured reasoning beyond LLMs • Enabling multi-agent collaborative intelligence in Web3 This grants @TheoriqAI a strong differentiated position in the “Agentic AI + Crypto” space. With future developer tools or SDKs, it could become a foundational layer for decentralized AI collaboration. @TheoriqAI @KaitoAI