AISAC：一个集成的多智能体系统，用于透明、基于检索的科学协助
AISAC: An Integrated multi-agent System for Transparent, Retrieval-Grounded Scientific Assistance
AI总结：
AISAC 提供了一个透明的多智能体运行环境，支持长期的证据支持科学推理，通过结构化保证实现角色语义、预算管理、可追溯执行和工具交互可重复性。
摘要：
AI 科学助手核心（AISAC）是阿贡国家实验室开发的透明、模块化的多智能体运行时系统，旨在支持长期的证据支持科学推理。AISAC 不提出新的智能体算法或声称自主科学发现，而是提供一个受控执行子系统，实现了部署智能体AI在科学实践中的关键要求，包括显式角色语义、预算化的上下文管理、可追溯执行以及与工具和知识的可重复交互。AISAC 强制执行四个结构保证：（1）声明性的智能体注册，具有运行时强制的角色语义和自动系统提示生成；（2）通过显式的每回合上下文和委托深度限制进行预算化编排；（3）在片段、对话和证据层之间实现角色对齐的内存访问；（4）通过持久执行记录和实时事件流接口实现基于追踪的透明性。这些保证通过混合持久内存（SQLite和双FAISS索引）、受控检索（智能体范围RAG）、结构化工具执行（模式验证）以及配置驱动的启动机制实现，该机制允许项目特定的扩展而无需修改共享核心。AISAC 目前在阿贡的多个科学流程中部署，包括燃烧科学、材料研究和能源过程安全，展示了其作为领域专用AI科学助手的可重用子系统。
英文摘要：
AI Scientific Assistant Core (AISAC) is a transparent, modular multi-agent runtime developed at Argonne National Laboratory to support long-horizon, evidence-grounded scientific reasoning. Rather than proposing new agent algorithms or claiming autonomous scientific discovery, AISAC contributes a governed execution substrate that operationalizes key requirements for deploying agentic AI in scientific practice, including explicit role semantics, budgeted context management, traceable execution, and reproducible interaction with tools and knowledge. AISAC enforces four structural guarantees for scientific reasoning: (1) declarative agent registration with runtime-enforced role semantics and automatic system prompt generation; (2) budgeted orchestration via explicit per-turn context and delegation depth limits; (3) role-aligned memory access across episodic, dialogue, and evidence layers; and (4) trace-driven transparency through persistent execution records and a live event-stream interface. These guarantees are implemented through hybrid persistent memory (SQLite and dual FAISS indices), governed retrieval with agent-scoped RAG, structured tool execution with schema validation, and a configuration-driven bootstrap mechanism that enables project specific extension without modifying the shared core. AISAC is currently deployed across multiple scientific workflows at Argonne, including combustion science, materials research, and energy process safety, demonstrating its use as a reusable substrate for domain-specialized AI scientific assistants.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
