什么是知识表示？
What is knowledge representation?
知识表示研究怎样用计算机能处理的形式来描述事实、概念和关系，例如一阶逻辑、语义网络和框架。好的表示能让推理更高效、知识更易复用与共享。
Knowledge representation studies how to encode facts, concepts, and relations in forms computers can process, such as first-order logic, semantic networks, and frames. Good representations make reasoning more efficient and knowledge easier to reuse and share.
难度 专业 · 适合 高中(15-18)
CC BY 4.0 · 已核验 · Verified 2026-08-23 · 2 条独立证据
来源 · Source
Russell & Norvig,《Artificial Intelligence: A Modern Approach》第4版,Pearson,2020
S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 4th ed., Pearson, 2020
独立核验依据 · Independent verification: 核验依据 2 ARCHIVE 标识 isbn_9788177583670：Artificial Intelligence: A
#知识表示 #语义网络 #逻辑
AlphaGo 是如何战胜人类顶尖围棋棋手的？
How did AlphaGo defeat top human Go players?
AlphaGo 由 DeepMind 开发，结合深度神经网络与强化学习，并用蒙特卡洛树搜索（MCTS）在每一步评估与探索落子。它先在人类棋谱上监督学习，再通过自我对弈强化学习持续提升，于 2016 年在《自然》发表并击败李世石。这标志着 AI 在搜索空间极其庞大的复杂博弈中首次超越人类顶尖水平。
Developed by DeepMind, AlphaGo combined deep neural networks with reinforcement learning and used Monte Carlo tree search (MCTS) to evaluate and explore moves each turn. It first learned from human games via supervised learning, then improved through self-play reinforcement learning, and in 2016 (published in Nature) defeated Lee Sedol. This marked the first time AI surpassed top human play in a game with an astronomically large search space.
难度 专业 · 适合 高中(15-18)
CC BY 4.0 · 来源待核验 · Source pending review
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出处备注：此条未指向带版次的可引用著作（通识性内容、机构文件或未展开的英文书名），本库不提供独立书目出处；如需精确引用，需由编辑补全具体篇目与版次。
Silver 等 2016（Nature）；DeepMind
Silver et al. (2016), Nature; DeepMind
#AlphaGo #强化学习 #蒙特卡洛树搜索 #DeepMind
什么是知识图谱？
What is a knowledge graph?
知识图谱用「实体—关系—实体」的三元组来表示现实世界中的知识，形成可机器推理的网络。它能支撑搜索引擎的语义理解、智能问答和推荐系统。维基数据和 Google 知识图谱是著名例子。
A knowledge graph represents real-world knowledge as triples of entity-relation-entity, forming a network that machines can reason over. It supports semantic understanding in search engines, intelligent Q&A, and recommendation systems. Wikidata and Google's Knowledge Graph are well-known examples.
难度 专业 · 适合 高中(15-18)
CC BY 4.0 · 已核验 · Verified 2026-08-23 · 2 条独立证据
来源 · Source
Russell & Norvig,《Artificial Intelligence: A Modern Approach》第4版,Pearson,2020
S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 4th ed., Pearson, 2020
独立核验依据 · Independent verification: 核验依据 2 ARCHIVE 标识 isbn_9788177583670：Artificial Intelligence: A
#知识图谱 #实体 #语义
A* 搜索算法是什么？它相比迪杰斯特拉好在哪里？
What is the A* search algorithm, and how is it better than Dijkstra?
A* 是带启发式的图搜索算法，用估价函数 f(n)=g(n)+h(n) 同时考虑已走代价 g 与到目标的预估代价 h，从而有方向地搜索。相比迪杰斯特拉（等价于 h=0）盲目扩展所有方向，A* 在启发式可采纳时既能保证最优又能大幅减少扩展节点数。它由哈特、尼尔松与拉斐尔于 1968 年提出，广泛用于路径规划与游戏 AI。
A* is a heuristic graph-search algorithm using f(n)=g(n)+h(n), combining the cost so far g with a heuristic estimate h to the goal, so it searches directionally. Compared with Dijkstra (equivalent to h=0), which expands blindly in all directions, A* with an admissible heuristic remains optimal yet expands far fewer nodes. Proposed by Hart, Nilsson, and Raphael in 1968, it is widely used in pathfinding and game AI.
难度 专业 · 适合 高中(15-18)
CC BY 4.0 · 已核验 · Verified 2026-11-03
来源 · Source
Hart, Nilsson & Raphael 1968；Russell & Norvig《人工智能：现代方法》
Hart, Nilsson & Raphael (1968); Russell & Norvig, Artificial Intelligence: A Modern Approach
独立核验依据 · Independent verification: 核验依据 1 ARCHIVE 标识 isbn_9788177583670：Artificial Intelligence: A
#A*算法 #启发式 #最佳优先搜索 #路径规划
什么是「智能体」（Agent）？
What is an agent?
在 AI 中，智能体是能感知环境并采取行动以实现目标的系统，小到扫地机器人，大到软件聊天程序。现代「智能体」常结合大语言模型，能自主规划、调用工具完成任务。它强调感知—思考—行动的闭环。
In AI, an agent is a system that perceives its environment and takes actions to achieve goals, from a vacuum robot to a chat program. Modern agents often combine large language models and can autonomously plan and use tools to finish tasks. The emphasis is on the perceive-think-act loop.
难度 进阶 · 适合 初中(12-15)
CC BY 4.0 · 来源待核验 · Source pending review
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出处备注：此条未指向带版次的可引用著作（通识性内容、机构文件或未展开的英文书名），本库不提供独立书目出处；如需精确引用，需由编辑补全具体篇目与版次。
AI 与自动化系统概念
Concept in AI and autonomous systems
#智能体 #Agent #自主
什么是自然语言处理？
What is natural language processing?
自然语言处理（NLP）是让计算机理解、生成和处理人类语言的技术，涵盖翻译、问答、情感分析等任务。现代 NLP 大量使用深度学习模型来捕捉语言的语义。它是人机对话和搜索引擎的重要支撑。
Natural language processing (NLP) lets computers understand, generate, and manipulate human language, covering tasks like translation, question answering, and sentiment analysis. Modern NLP heavily uses deep learning models to capture meaning. It underpins conversational agents and search engines.
难度 进阶 · 适合 初中(12-15)
CC BY 4.0 · 已核验 · Verified 2026-08-23 · 2 条独立证据
来源 · Source
Russell & Norvig,《Artificial Intelligence: A Modern Approach》第4版,Pearson,2020
S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 4th ed., Pearson, 2020
独立核验依据 · Independent verification: 核验依据 2 ARCHIVE 标识 isbn_9788177583670：Artificial Intelligence: A
#自然语言处理 #NLP #语言
什么是专家系统？
What is an expert system?
专家系统是早期 AI 的一种，把领域专家的知识写成「规则」，再由推理引擎根据事实得出结论，常用于医疗诊断或故障排查。它能在特定领域内模拟专家的决策过程。缺点是知识获取困难、难以覆盖复杂情况。
An expert system is an early form of AI that encodes a domain expert's knowledge as rules, then uses an inference engine to draw conclusions from facts, often for medical diagnosis or fault finding. It can simulate an expert's decision process within a narrow field. Its drawbacks are difficult knowledge acquisition and limited coverage of complex situations.
难度 进阶 · 适合 初中(12-15)
CC BY 4.0 · 已核验 · Verified 2026-08-23 · 2 条独立证据
来源 · Source
Russell & Norvig,《Artificial Intelligence: A Modern Approach》第4版,Pearson,2020
S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 4th ed., Pearson, 2020
独立核验依据 · Independent verification: 核验依据 2 ARCHIVE 标识 isbn_9788177583670：Artificial Intelligence: A
#专家系统 #规则 #推理
什么是启发式方法？
What is a heuristic?
启发式是在信息不全或时间有限时，用经验规则快速逼近满意解的方法，不保证最优但常足够好。下棋程序用局面评估、导航用朝目标直线走都是典型启发式。
A heuristic is a rule of thumb that quickly reaches a satisfactory solution when information is incomplete or time is limited; it need not be optimal but is often good enough. Chess programs use position evaluation and navigation uses heading straight toward the goal as typical heuristics.
难度 进阶 · 适合 初中(12-15)
CC BY 4.0 · 已核验 · Verified 2026-08-23 · 2 条独立证据
来源 · Source
Russell & Norvig,《Artificial Intelligence: A Modern Approach》第4版,Pearson,2020
S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 4th ed., Pearson, 2020
独立核验依据 · Independent verification: 核验依据 2 ARCHIVE 标识 isbn_9788177583670：Artificial Intelligence: A
#启发式 #经验规则 #近似解
人工智能中的搜索树是什么？
What is a search tree in AI?
搜索树把问题从初始状态到目标状态的可能步骤展开成一棵树，每个节点是一种状态。AI 通过深度优先、广度优先或 A* 等策略在树上寻找解路径，A* 还借助启发式优先扩展更有希望的分支。
A search tree expands a problem's possible steps from an initial state to a goal into a tree where each node is a state. AI searches for a solution path using strategies like depth-first, breadth-first, or A*, where A* uses a heuristic to expand promising branches first.
难度 进阶 · 适合 初中(12-15)
CC BY 4.0 · 已核验 · Verified 2026-08-23 · 2 条独立证据
来源 · Source
Russell & Norvig,《Artificial Intelligence: A Modern Approach》第4版,Pearson,2020
S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 4th ed., Pearson, 2020
独立核验依据 · Independent verification: 核验依据 2 ARCHIVE 标识 isbn_9788177583670：Artificial Intelligence: A
#搜索树 #状态空间 #A*
图灵测试（Turing Test）想检验什么？
What does the Turing Test aim to check?
图灵测试由艾伦·图灵在 1950 年发表于《Mind》的论文中提出：如果人类通过纯文字对话无法分辨对方是机器还是人，就可认为该机器表现出智能。它把抽象的「机器能否思考」转化为可操作的外部行为判据。该测试长期作为 AI 的哲学与工程参照，但也因只考察表面行为、忽略真实理解与具身性而受到批评。
Proposed by Alan Turing in 1950, the test posits that if a human cannot tell from text-only conversation whether the other party is a machine or a person, the machine may be said to exhibit intelligence. It reframes the abstract question 'can machines think' into an operational behavioral criterion. Long a philosophical and engineering reference for AI, it is also criticized for ignoring genuine understanding and embodiment.
难度 进阶 · 适合 初中(12-15)
CC BY 4.0 · 已核验 · Verified 2026-11-02
来源 · Source
Turing 1950《Computing Machinery and Intelligence》（Mind 59(236)）；Russell & Norvig《人工智能：现代方法》
Turing (1950), 'Computing Machinery and Intelligence', Mind 59(236); Russell & Norvig, Artificial Intelligence: A Modern Approach
独立核验依据 · Independent verification: 核验依据 1 OPENLIBRARY 标识 /works/OL12856938W：Computing machinery an
#图灵测试 #图灵 #机器智能 #行为判据
什么是图灵测试？
What is the Turing test?
图灵测试由阿兰·图灵在 1950 年提出，用来判断机器是否表现出与人无异的智能。测试者通过文字与机器和真人交谈，若无法分辨哪边是机器，则该机器被认为通过了测试。它是 AI 领域最具代表性的思想实验。
Proposed by Alan Turing in 1950, the Turing test judges whether a machine exhibits human-like intelligence. A tester converses by text with both a machine and a human; if unable to tell which is which, the machine is said to pass. It is the most representative thought experiment in AI.
难度 入门 · 适合 大众
CC BY 4.0 · 来源待核验 · Source pending review
来源 · Source
出处备注：著录含书名，但缺版次 / 出版社 / 年份中的一部分，需编辑补全后才能做独立比对。
图灵 1950 年论文《计算机器与智能》
Turing's 1950 paper Computing Machinery and Intelligence
#图灵测试 #智能 #图灵
机器能像人一样学习吗？
Can machines learn like humans?
可以，但不是靠读书，而是从大量数据中总结规律。例如给它看成千上万张猫的照片，它就能学会认出猫。这种「从例子中学习」的方法叫机器学习，是人工智能的重要部分。
Yes, but not by reading books; they find patterns from large amounts of data. For example, after seeing thousands of cat photos, a model can learn to recognize cats. This learning-from-examples method is called machine learning and is an important part of AI.
难度 入门 · 适合 小学高段(9-12)
CC BY 4.0 · 来源待核验 · Source pending review
来源 · Source
出处备注：作者 / 书名 / 版次 / 出版社 / 年份齐备，仅缺独立比对证据；已在可信度报告单列披露，不再重复核验。
Mitchell, T. M. (1997). 《机器学习》. McGraw-Hill.
Mitchell, T. M. (1997). Machine Learning. McGraw-Hill.
#机器学习 #学习 #数据
电脑能看吗？
Can computers see?
电脑本身不会用眼睛看，但装上摄像头并运行视觉程序后，它能认出照片里的小猫或红绿灯。这就像给它配了一双电子眼，帮它理解看到的图像。
A computer can't literally see with eyes, but with a camera and vision software it can recognize a cat or a traffic light in a photo. It's like giving it electronic eyes to understand what it sees.
难度 入门 · 适合 幼儿(3-6)
CC BY 4.0 · 已核验 · Verified 2026-08-23 · 2 条独立证据
来源 · Source
Russell & Norvig,《Artificial Intelligence: A Modern Approach》第4版,Pearson,2020
S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 4th ed., Pearson, 2020
独立核验依据 · Independent verification: 核验依据 2 ARCHIVE 标识 isbn_9788177583670：Artificial Intelligence: A
#视觉 #图像 #识别
人工智能（AI）一般指什么？
What does artificial intelligence (AI) generally mean?
人工智能指让机器表现出通常需要人类智能的行为，如理解语言、识别图像、推理决策和学习。「人工智能」一词最早出现在麦卡锡、明斯基、罗切斯特与香农 1955 年撰写的达特茅斯会议提案中，1956 年夏举行的达特茅斯会议被视为该领域诞生的标志。现代 AI 大量依赖机器学习与数据驱动方法，而非仅靠手工规则。
Artificial intelligence means building machines that exhibit behaviors usually requiring human intelligence, such as understanding language, recognizing images, reasoning, deciding, and learning. The term first appeared in the 1955 proposal for the Dartmouth workshop written by McCarthy, Minsky, Rochester, and Shannon, and the summer 1956 workshop is regarded as the birth of the field. Modern AI relies heavily on machine learning and data-driven methods rather than hand-coded rules alone.
难度 入门 · 适合 大众
CC BY 4.0 · 已核验 · Verified 2026-11-03
来源 · Source
McCarthy, Minsky, Rochester & Shannon 1955《达特茅斯人工智能夏季研究项目提案》；Russell & Norvig《人工智能：现代方法》
McCarthy, Minsky, Rochester & Shannon (1955), 'A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence'; Russell & Norvig, Artificial Intelligence: A Modern Approach
独立核验依据 · Independent verification: 核验依据 1 ISBN 9787115598103（豆瓣书目条目: 人工智能现代方法）；本条出处含多部著作，此标识只担保上面点
#人工智能 #达特茅斯会议 #麦卡锡 #智能
什么是计算机视觉？
What is computer vision?
计算机视觉是让机器「看懂」图像和视频的技术，包括识别物体、检测人脸、理解场景等。它结合了图像处理和机器学习，是自动驾驶、医疗影像分析和安防的核心。近年来深度学习大幅提升了其准确率。
Computer vision is the technology that lets machines see images and video, including recognizing objects, detecting faces, and understanding scenes. It combines image processing with machine learning and is central to self-driving, medical imaging, and security. Deep learning has greatly improved its accuracy in recent years.
难度 入门 · 适合 大众
CC BY 4.0 · 已核验 · Verified 2026-08-23 · 2 条独立证据
来源 · Source
Russell & Norvig,《Artificial Intelligence: A Modern Approach》第4版,Pearson,2020
S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 4th ed., Pearson, 2020
独立核验依据 · Independent verification: 核验依据 2 ARCHIVE 标识 isbn_9788177583670：Artificial Intelligence: A
#计算机视觉 #图像 #识别
扫地机器人怎么知道哪里没扫过?它会迷路吗?
How does a robot vacuum know where it cleaned? Can it get lost?
扫地机器人有小眼睛(传感器),一边跑一边给家里画地图,像你玩迷宫记住走过的路。碰到桌腿就说声抱歉绕开,电量低了还会自己回家充电呢!
A robot vacuum has little eyes — sensors — that draw a map as it goes, like remembering your way through a maze. It steers around table legs and drives home to charge when battery runs low.
难度 入门 · 适合 幼儿(3-6)
CC BY 4.0 · 已核验 · Verified 2026-10-04
来源 · Source
《概率机器人》Thrun等，MIT Press，2005
Probabilistic Robotics, Thrun, Burgard & Fox, MIT Press, 2005
独立核验依据 · Independent verification: 核验依据 1 ISBN 9780262332750 (2005)
#机器人 #传感器 #地图