????????UNIT 1 Introduction to Artificial Intelligence

????????????????AI, Artificial Intelligence 人工智能

????????????????The Turing Test 圖靈測試：The test is based on whether a computer can fool a

????????????????human into believing it is another human.?

????????????????這項測試是基于計算機是否能夠欺騙人類，使其相信它是另一個人類。

????????????????benchmark 基準

????????????????The benefits and risks of AI ?

????????????????narrow AI 狹義人工智能（弱人工智能）

????????????????general AI (AGI or strong AI) 通用人工智能（強人工智能）

????????????????side effect 副作用

????????????????malevolence /?competence惡意/能力

????????Unit 2 Knowledge Representation and Reasoning?知識的表示與推理

????????????????Perception 感知

????????????????warehouse of knowledge 知識倉庫

????????????????declarative and procedural forms 聲明性和程序性形式

????????????????spectrum 范圍

????????????????semantic net 語義網(wǎng)

????????????????contextual analysis 上下文分析

????????????????implicitly/explicitly 隱式/顯示

????????????????retrieve ?檢索

????????????????related information and relevant information 相關(guān)信息和有關(guān)信息

????????????????knowledge extraction system 知識提取系統(tǒng)

????????????????closed-world assumption 封閉世界假設(shè)

????????????????open-world assumption 開放世界假設(shè)

????????????????derived from ?來自

????????????????meta-reasoning 元推理

????????????????intelligent agent 智能代理/體

????????????????learning by imitation ?模仿學習

????????????????supervised learning 監(jiān)督學習

????????????????unsupervised learning 無監(jiān)督學習

????????????????training set 訓練集

????????????????learning by reinforcement 強化學習

????????????????trial and error 試錯

????????????????rely?heavily on 嚴重依賴于

????????????????data mining agent 數(shù)據(jù)挖掘代理

????????????????conservation of momentum 動量守恒

????????????????infrared spectral?紅外光譜

????????UNIT 3 Reasoning with Uncertainty

????????????????knowledge representation and reasoning 知識表示與推理

????????????????truth value 真值

????????????????semantic explanation 語義解釋

????????????????formal language 形式語言

????????????????a set of inference rules 一組推理規(guī)則

????????????????memory-control mechanism 內(nèi)存控制機制

????????????????monotonic 單調(diào)

????????????????axiom 公理

????????????????theorem?定理

????????????????plausible reasoning 合情推理

????????????????non-monotonic logics 非單調(diào)邏輯

????????????????commonsense reasoning 常識推理

????????????????consistency 一致性

????????????????the relevant conclusion 相關(guān)推論

????????????????knowledge base 知識庫

????????????????truth maintenance system?真值維護系統(tǒng)

????????????????Bayes' Theorem 貝葉斯定理?

????????????????fuzzy logic 模糊邏輯

????????????????imprecision 不精確

????????????????a degree of membership 隸屬度

????????????????general-purpose 多用途的

????????????????uncertainty reasoning?不確定性推理

????????????????probabilistic reasoning?概率推理

????????????????prepositional logic?命題邏輯

????????????????conditional probabilities 條件概率

????????????????strength of dependency?依賴強度

????????????????directed acyclic graph?有向無向圖

????????????????Bayesian Network 貝葉斯網(wǎng)絡(luò)

????????????????貝葉斯網(wǎng)絡(luò)是有向無環(huán)圖，其中節(jié)點表示關(guān)注變量，鏈接表示變量之間的信息或因果

????????????????相關(guān)性。依賴的強度由條件概率表示。與其他概率推理方法相比，貝葉斯網(wǎng)絡(luò)（圖3-1）

????????????????效率更高，盡管對于復雜問題，其實際計算成本仍然很高。

????????????????prior probability 先驗概率

????????????????the posterior probability 后驗概率

????????????????rule-based systems 規(guī)則庫系統(tǒng)

????????UNIT 4 Search Method in Artificial Intelligent

????????????????uninformed search?無信息搜索

????????????????breadth-first search 廣度優(yōu)先搜索

????????????????heuristic rating啟發(fā)式評級

????????????????search tree 搜索樹

????????????????heuristic Search?啟發(fā)式搜索

????????????????search space?搜尋空間

????????????????cost estimate function 成本估算函數(shù)

????????UNIT 5 Machine Learning

????????????????candidate solutions 候選解

????????????????potential solutions 期望解

????????????????non-deterministic 非確定的

????????????????Recombination?重組

????????????????Crossover?交叉

????????????????individuals 個人

????????????????Mutation?突變

????????????????fitness function?適應(yīng)度函數(shù)

????????????????evolutionary algorithm?進化算法

????????????????population of individuals?群體

????????????????cost estimate function 成本估算函數(shù)

????????????????a traversal of the entire search space?整個搜索空間的遍歷

????????????????depth-first and breadth- first search?深度優(yōu)先和廣度優(yōu)先探索

????????????????k-means clustering k均值聚類

????????????????linear regression algorithm?線性回歸算法

????????????????decision tree?決策樹

????????UNIT 6 Artificial Neural Networks

????????????????Nonlinear activation function?非線性激活函數(shù)

????????????????Feedforward neural network?前饋神經(jīng)網(wǎng)絡(luò)

????????????????threshold value?閾值

????????????????the activities within a neuron?神經(jīng)元內(nèi)的活動

????????????????weighted sum 加權(quán)總和

????????????????hidden layers?隱藏層

????????????????nearest-neighbor approach?最近鄰法

????????????????cross-validation交叉驗證

????????????????down-sampling下采樣

????????????????affine transformation 仿射變換

????????UNIT 7 Deep Learning

????????????????LSTM?長短期記憶網(wǎng)絡(luò)Long Short-Term Memory

????????????????Multilayer perceptron?多層感知器

????????????????Convolutional neural networks, CNN?卷積神經(jīng)網(wǎng)絡(luò)

????????????????RNN?循環(huán)神經(jīng)網(wǎng)絡(luò)Recurrent Neural Network

????????????????Graph neural network?圖神經(jīng)網(wǎng)絡(luò)

????????????????max pooling?最大池化

????????????????average pooling?平均池化

????????????????fully connected layer?全鏈接層

????????????????convolutional layer?卷積層

????????????????receptive field?感受野

????????????????Feedforward neural network?前饋神經(jīng)網(wǎng)絡(luò)

????????????????Deep Learning，Machine Learning and AI?深度學習，機器學習，人工智能

????????????????object detection?對象檢測

????????UNIT 8 Reinforcement Learning

????????????????reinforcement learning?強化學習

????????????????Markov decision process?馬爾可夫決策過程

????????????????AlphaGo Zero阿爾法元

?????????????????Artificial General Intelligence/AGI 通用人工智能

????????????????Iteration?迭代

????????????????more prevalent and sophisticated?更加普遍和復雜

????????????????without being explicitly "taught"?沒有明確地教導

????????????????deep reinforcement learning?深度強化學習

????????????????hidden patterns?隱藏的模式

????????????????Overestimate?高估

????????????????venture into?冒險進入

????????UNIT 9 Computer Vision

????????????????computer vision?計算機視覺

????????????????edge detection?邊緣探測

????????????????temporal information?時間信息

????????????????SVM支持向量機（Support Vector Machine, SVM）

????????????????lateral control?橫向控制

????????????????steering-control system?轉(zhuǎn)向控制系統(tǒng)

????????????????longitudinal control?縱向控制

????????????????optical flow?光流

????????????????binocular stereopsis?雙目立體視覺

????????????????IMU?Inertial Motion Unit?慣性運動單元

????????????????Kalman filtering?卡爾曼濾波

????????????????visual odometry?視覺里程計

????????????????accuracies on the order of centimete?厘米級精度

????????????????errors accumulating over time?錯誤隨時間積累

????????UNIT 10 Natural Language Processing

????????????????NLP?自然語言處理Natural Language Processing

????????????????Backus-Naur Form/巴科斯范式

????????????????Chomsky?’s Linguistics?喬姆斯基語言學

????????????????CS?Code Segment?代碼段首址寄存器

????????????????sentiment analysis?情感分析

????????????????speech recognition 語音識別

????????????????syntactic analysis/syntax analysis/semantic analysis/pragmatic analysis

????????????????句法分析/句法分析/語義分析/語用分析

????????????????Syntax?句法

????????????????parse/parser/parse tree 解析/解析器/解析樹

????????????????predicate logic 謂詞邏輯

????????????????Ambiguities模棱兩可

????????????????information extraction信息提取

????????????????information retrieval信息檢索

????????????????statistical techniques 統(tǒng)計技術(shù)

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