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- Level Foundation
- المدة
- الطبع بواسطة National Taiwan University
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Offered by
عن
本課程分為人工智慧（上）、人工智慧（下）兩部份，第一部分除了人工智慧概論外，著重在目標搜尋、meta heuristic、電腦對弈、演繹學習（包含證言邏輯、一階邏輯及 planning ）等技術。這些技術主要發展時機為人工智慧的第一波及第二波熱潮，也就是 1950 年代至 1990 年代附近的主流發展，即使到現在也在各個領域廣為應用。 課程教學目標： 使同學對人工智慧有基礎概念 同學能夠理解如何運用目標搜尋技術及演繹學習方式達成人工智慧 同學能將相關技術應用到自己的問題上الوحدات
Course Videos
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9
Videos
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1
Readings
9
Videos
- 1-1 History of AI：TuringTest and Its Application, Chinese Room Argument
- 1-2 What is AI
- 1-3 Agents and Environments, PEAS, Environment Type
- 1-4 Different Level Of AI
- 1-5 Wave of AI：Debut, Knowledge Driven, Data Driven
- 1-6 The Classification of Agent, First Wave of AI (Artificial Neural Network)
- 1-7 Second Wave of AI (Expert System)
- 1-8 Third Wave of AI (Some Theory and Principle of Machine Learning)
- 1-9 Conclusion of AI and Machine Learning
1
Readings
- NTU MOOC 課程問題詢問與回報機制
Course Videos
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6
Videos
6
Videos
- 2-1 Problem Solving Agents, Problem Formulation (i)
- 2-2 Problem Formulation (ii) - Abstraction
- 2-3 Search on Tree and Graph
- 2-4 Uninformed Search (i) - Breadth-First Search, Uniform-Cost Search
- 2-5 Uninformed Search (ii) - Depth-First Search, Depth-Limited Search, Iterative-Deepening Search
- 2-6 Uninformed Search (iii) - Iterative-Deepening Search, Bidirectional Search
Quiz
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1
Assignment
1
Assignment
- Week 2
Course Videos
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6
Videos
6
Videos
- 3-1 Best-First Search (i) - Greedy Search
- 3-2 Best-First Search (ii) - A* Search
- 3-3 Best-First Search (iii) - Optimality of A*
- 3-4 Memory Bounded Search (i) - Iterative Deepening A*, RBFS
- 3-5 Memory Bounded Search (ii) - RBFS, Simplified Memory-bounded A*
- 3-6 Heuristic - Preformance, Generating Heuristics
Quiz
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1
Assignment
1
Assignment
- Week 3
Course Videos
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7
Videos
7
Videos
- 4-1 Black-Box Optimization
- 4-2 Steepest Descent
- 4-3 Simulated Annealing
- 4-4 Evolutionary Computation
- 4-5 Non-deterministic Actions - AND-OR Search, Partial Observations (i) - Sensor-less
- 4-6 Partial Observations (ii) - With Sensors
- 4-7 Partial Observations (iii) - Unknown Environments
Quiz
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1
Assignment
1
Assignment
- Week 4
Course Videos
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6
Videos
6
Videos
- 5-1 Type of Games - Symbols, Game Tree
- 5-2 Optimal Decision, Negamax Search , Alpha-Beta Pruning (i)
- 5-3 Alpha-Beta Pruning (ii)
- 5-4 Asperasion Windows, NegaScout
- 5-5 Imperfect Decisions, Forward Pruning
- 5-6 Stochastic Games, Partially Observable Games
Quiz
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1
Assignment
1
Assignment
- Week 5
Course Videos
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7
Videos
7
Videos
- 6-1 Logical Agents (i) - Generic Knowledge-Based Agent, PEAS
- 6-2 Logical Agents (ii) - Logic, Entailment and Models
- 6-3 Propositional Logic, Inference (i) - Enumeration, Validity and Satisfiability
- 6-4 Inference (ii) - Simple Knowledge, Resolution and CNF (i) - Proof by Resolution, CNF Conversion, Resolution Algorithm
- 6-5 Resolution and CNF (ii) - Properties of Resolution, Ground Resolution Theorem
- 6-6 Resolution and CNF (iii) - Horn and Definite Clauses, Forward Chaining
- 6-7 Backward Chaining, Pros and Cons of Propositional Logic
Quiz
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1
Assignment
1
Assignment
- Week 6
Course Videos
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8
Videos
8
Videos
- 7-1 First-Order Logic (i) - Syntax of FOL and Semantics
- 7-2 First-Order Logic (ii) - Using FOL, Inference (i) - Instantiation
- 7-3 Inference (ii) - Propositionalization, Inference (iii) - Unification
- 7-4 Inference (iii) - Unification, Inference (iv) - Forward chaining
- 7-5 Inference (iv) - Forward chaining, Inference (v) - Backward chaining
- 7-6 Logic Programing (i) - Prolog Systems
- 7-7 Logic Programing (ii) - Redundant Inference and Infinite Loops in Prolog
- 7-8 Inference (vi) - Resolution
Quiz
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1
Assignment
1
Assignment
- Week 7
Course Videos
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6
Videos
6
Videos
- 8-1 Planning Domain Definition Language (PDDL) (i)
- 8-2 Planning Domain Definition Language (PDDL) (ii)
- 8-3 State-Space Search, Heuristics
- 8-4 Planning Graphs
- 8-5 GRAPHPLAN
- 8-6 Course Review
Quiz
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1
Assignment
1
Assignment
- Week8
【補充教材】
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1
Readings
1
Readings
- 臺大開放式課程（NTU OpenCourseWare）：計算機概論
Instructor
于天立