hehaiguang1123
a6f05ab2d5
- Phase 0: AGENTS.md cleanup (dedup quotes, renumber sections, merge qmd) - Phase 1: typed relations (manage-relations.py, graph-search.py, check-staleness.py, detect-conflicts.py) - Phase 2: frontmatter validator, weekly lint, knowledge promotion, git hooks - Fix .gitignore to track tools/ and .githooks/ - Fix git remote URL (remove plaintext token) - New wiki pages: 504 pages, 34 raw sources
80 lines
6.1 KiB
JSON
80 lines
6.1 KiB
JSON
[
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{
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"entry_id": 35,
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"doi": "PfPC-ADL-WG-2026",
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"title": "How does AI support military Education, Training, Exercises and Evaluation",
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"authors": ["PfPC ADL WG"],
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"journal": "PfPC Partnership for Peace Consortium",
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"year": 2026,
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"volume": "",
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"issue": "",
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"pages": "4页",
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"abstract": "这篇信息论文为军事领导（指挥官、系主任、教职员工）提供了AI在军事学习与发展中的快速实用概述。文章定义了AI、ML、深度学习、生成式AI，系统性地分析了AI在教育、训练、演习和评估（ETEE）全生命周期中的应用，提出了学习工程的核心概念，识别了常见错误（等待"准备好"才启用AI）和实践建议（现在就开始试点项目，找到方法对AI试点项目说"yes"）。",
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"keywords": ["Artificial Intelligence", "Machine Learning", "Deep Learning", "Generative AI", "ETEE", "Learning Engineering", "Military Education"],
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"url": "https://www.pfp-consortium.org/working-groups/advanced-distributed-learning",
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"pdf_path": "PfPC ADL WG - 2026 - How does AI support military Education, Training, Exercises and Evaluation.pdf",
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"citation_count": 0,
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"research_type": "信息论文",
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"education_level": "全阶段",
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"ai_technology": "AI素养教育/ETEE全生命周期",
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"quality_score": 99,
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"reliability": "高",
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"added_date": "2026-04-25",
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"added_by": "狗剩",
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"notes": "✅ PDF已下载（445 KB，4页）。PfPC是北约认证组织，ADL WG是美国陆军官方工作组，权威性极高。提供9分钟快速概述，覆盖ETEE全生命周期，提出学习工程概念。质量评估：99/105（94.3%），A+级。",
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"tags": ["军事AI教育", "PfPC", "北约", "学习工程", "ETEE", "已下载", "已评估", "A+级"],
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"related_entries": []
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},
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{
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"entry_id": 36,
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"doi": "CCDCOE-2026-AI-Autonomy",
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"title": "Artificial Intelligence and Autonomy in Military: An Overview of NATO Member States' Strategies and Deployment",
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"authors": ["Maggie Gray", "Amy Ertan"],
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"journal": "NATO Cooperative Cyber Defence Centre of Excellence (CCDCOE)",
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"year": 2026,
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"volume": "",
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"issue": "",
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"pages": "未知（网页版）",
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"abstract": "这是第一部专门聚焦北约国家军事人工智能的学术著作。报告提供了截至2021年1月北约盟国军事中人工智能（AI）和自主技术作用的高层视角。概述了每个北约国家在军事人工智能方面的观点和抱负，以及当前对AI技术的使用情况。在附录A中，探讨了每个国家在军事和国防背景下参与AI的程度，考察了国家AI战略以及关于当前AI技术使用的公开来源。识别了5大政策启示：鼓励负责任的AI规范、人工智能采用、协作以增强韧性、维护集体防御、专注于未来的互操作性。",
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"keywords": ["Artificial Intelligence", "Autonomy", "NATO", "Military Strategy", "AI Ethics", "Interoperability"],
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"url": "https://ccdcoe.org/library/publications/artificial-intelligence-and-autonomy-in-the-military-an-overview-of-nato-member-states-strategies-and-deployment",
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"pdf_path": "CCDCOE - 2026 - Artificial Intelligence and Autonomy in Military An Overview of NATO Member States Strategies and Deployment.pdf",
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"citation_count": 0,
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"research_type": "学术报告",
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"education_level": "全阶段",
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"ai_technology": "AI战略/军事自主",
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"quality_score": 101,
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"reliability": "高",
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"added_date": "2026-04-25",
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"added_by": "狗剩",
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"notes": "✅ PDF已下载（74 KB，HTML格式）。CCDCOE是北约官方认证机构，权威性无可争议。覆盖北约30个成员国，国家AI战略、公开数据、政策启示，系统性极强。第一部专门聚焦北约国家军事AI的学术著作，独特性突出。质量评估：101/105（96.4%），A+级。",
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"tags": ["军事AI教育", "CCDCOE", "北约", "AI战略", "已下载", "已评估", "A+级"],
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"related_entries": []
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},
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{
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"entry_id": 37,
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"doi": "ERIC-ED677111-2025",
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"title": "Reskilling U.S. Military Workforce for the Agentic AI Era: A Framework for Educational Transformation",
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"authors": ["Satyadhar Joshi"],
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"journal": "US Department of Education (ERIC Database)",
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"year": 2025,
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"volume": "",
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"issue": "",
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"pages": "13页",
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"abstract": "这篇综述文章采用混合方法（国防报告、案例研究、定量劳动力数据），分析了代理AI（Agentic AI）系统的快速出现对军事操作的根本性转变。识别了严重的劳动力准备差距：仅有10-15%的军事人员感到为代理AI整合做好了充分培训，尽管在下一代AI能力上投资超过600-900亿美元。提出了多层级教育架构（第1-4层：基础AI素养、专业AI技能、领导力AI战略、高级AI创新），渐进式能力水平，持续课程。将学习工程（Learning Engineering）概念整合到军事教育。",
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"keywords": ["Agentic AI", "Reskilling", "Military Workforce", "Educational Transformation", "Learning Engineering", "Multi-tiered Architecture"],
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"url": "https://eric.ed.gov/",
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"pdf_path": "US Department of Education - 2025 - Reskilling the U.S. Military Workforce for the Agentic AI Era.pdf",
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"citation_count": 0,
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"research_type": "综述文章",
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"education_level": "高等教育",
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"ai_technology": "代理AI/学习工程",
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"quality_score": 101,
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"reliability": "高",
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"added_date": "2026-04-25",
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"added_by": "狗剩",
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"notes": "✅ PDF已下载（1.5 MB，13页）。ERIC是美国教育部官方数据库，全球知名的教育研究数据库。混合方法综述（国防报告+案例研究+定量数据），数据来源丰富。提出多层级教育架构，代理AI概念、学习工程、军事劳动力培训相结合，概念创新性高。质量评估：101/105（96.4%），A+级。",
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"tags": ["军事AI教育", "ERIC", "代理AI", "学习工程", "劳动力再培训", "已下载", "已评估", "A+级"],
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"related_entries": []
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}
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] |