人工智慧：搜尋方法與邏輯推論 (Artificial Intelligence - Search & Logic)

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人工智慧：搜尋方法與邏輯推論 (Artificial Intelligence - Search & Logic)

Instructor: 于天立

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8 modules

Gain insight into a topic and learn the fundamentals.

322 reviews

Beginner level

No prior experience required

Flexible schedule

2 weeks at 10 hours a week

Learn at your own pace

95%

Most learners liked this course

8 modules

Gain insight into a topic and learn the fundamentals.

322 reviews

Beginner level

No prior experience required

Flexible schedule

2 weeks at 10 hours a week

Learn at your own pace

95%

Most learners liked this course

Skills you'll gain

Details to know

Shareable certificate

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Assessments

7 assignments

Taught in Chinese (Traditional)

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There are 8 modules in this course

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。

What's included

9 videos1 reading

9 videos Total 118 minutes

1-1 History of AI：TuringTest and Its Application, Chinese Room Argument 5 minutes
1-2 What is AI 16 minutes
1-3 Agents and Environments, PEAS, Environment Type 20 minutes
1-4 Different Level Of AI 5 minutes
1-5 Wave of AI：Debut, Knowledge Driven, Data Driven 6 minutes
1-6 The Classification of Agent, First Wave of AI (Artificial Neural Network) 25 minutes
1-7 Second Wave of AI (Expert System) 12 minutes
1-8 Third Wave of AI (Some Theory and Principle of Machine Learning) 21 minutes
1-9 Conclusion of AI and Machine Learning 8 minutes

1 reading Total 1 minute

NTU MOOC 課程問題詢問與回報機制 1 minute

What's included

6 videos1 assignment

6 videos Total 102 minutes

2-1 Problem Solving Agents, Problem Formulation (i) 15 minutes
2-2 Problem Formulation (ii) - Abstraction 18 minutes
2-3 Search on Tree and Graph 21 minutes
2-4 Uninformed Search (i) - Breadth-First Search, Uniform-Cost Search 18 minutes
2-5 Uninformed Search (ii) - Depth-First Search, Depth-Limited Search, Iterative-Deepening Search 14 minutes
2-6 Uninformed Search (iii) - Iterative-Deepening Search, Bidirectional Search 15 minutes

1 assignment Total 30 minutes

Week 2 30 minutes

What's included

6 videos1 assignment

6 videos Total 108 minutes

3-1 Best-First Search (i) - Greedy Search 16 minutes
3-2 Best-First Search (ii) - A* Search 17 minutes
3-3 Best-First Search (iii) - Optimality of A* 18 minutes
3-4 Memory Bounded Search (i) - Iterative Deepening A*, RBFS 22 minutes
3-5 Memory Bounded Search (ii) - RBFS, Simplified Memory-bounded A* 21 minutes
3-6 Heuristic - Preformance, Generating Heuristics 15 minutes

1 assignment Total 30 minutes

Week 3 30 minutes

What's included

7 videos1 assignment

7 videos Total 119 minutes

4-1 Black-Box Optimization 12 minutes
4-2 Steepest Descent 20 minutes
4-3 Simulated Annealing 13 minutes
4-4 Evolutionary Computation 19 minutes
4-5 Non-deterministic Actions - AND-OR Search, Partial Observations (i) - Sensor-less 19 minutes
4-6 Partial Observations (ii) - With Sensors 11 minutes
4-7 Partial Observations (iii) - Unknown Environments 24 minutes

1 assignment Total 16 minutes

Week 4 16 minutes

What's included

6 videos1 assignment

6 videos Total 118 minutes

5-1 Type of Games - Symbols, Game Tree 14 minutes
5-2 Optimal Decision, Negamax Search , Alpha-Beta Pruning (i) 19 minutes
5-3 Alpha-Beta Pruning (ii) 25 minutes
5-4 Asperasion Windows, NegaScout 17 minutes
5-5 Imperfect Decisions, Forward Pruning 24 minutes
5-6 Stochastic Games, Partially Observable Games 18 minutes

1 assignment Total 30 minutes

Week 5 30 minutes

What's included

7 videos1 assignment

7 videos Total 115 minutes

6-1 Logical Agents (i) - Generic Knowledge-Based Agent, PEAS 17 minutes
6-2 Logical Agents (ii) - Logic, Entailment and Models 21 minutes
6-3 Propositional Logic, Inference (i) - Enumeration, Validity and Satisfiability 19 minutes
6-4 Inference (ii) - Simple Knowledge, Resolution and CNF (i) - Proof by Resolution, CNF Conversion, Resolution Algorithm 19 minutes
6-5 Resolution and CNF (ii) - Properties of Resolution, Ground Resolution Theorem 12 minutes
6-6 Resolution and CNF (iii) - Horn and Definite Clauses, Forward Chaining 17 minutes
6-7 Backward Chaining, Pros and Cons of Propositional Logic 10 minutes

1 assignment Total 30 minutes

Week 6 30 minutes

What's included

8 videos1 assignment

8 videos Total 127 minutes

7-1 First-Order Logic (i) - Syntax of FOL and Semantics 16 minutes
7-2 First-Order Logic (ii) - Using FOL, Inference (i) - Instantiation 13 minutes
7-3 Inference (ii) - Propositionalization, Inference (iii) - Unification 18 minutes
7-4 Inference (iii) - Unification, Inference (iv) - Forward chaining 18 minutes
7-5 Inference (iv) - Forward chaining, Inference (v) - Backward chaining 13 minutes
7-6 Logic Programing (i) - Prolog Systems 18 minutes
7-7 Logic Programing (ii) - Redundant Inference and Infinite Loops in Prolog 13 minutes
7-8 Inference (vi) - Resolution 17 minutes

1 assignment Total 30 minutes

Week 7 30 minutes

What's included

6 videos1 reading1 assignment

6 videos Total 129 minutes

8-1 Planning Domain Definition Language (PDDL) (i) 22 minutes
8-2 Planning Domain Definition Language (PDDL) (ii) 26 minutes
8-3 State-Space Search, Heuristics 32 minutes
8-4 Planning Graphs 27 minutes
8-5 GRAPHPLAN 12 minutes
8-6 Course Review 10 minutes

1 reading Total 10 minutes

臺大開放式課程（NTU OpenCourseWare）：計算機概論 10 minutes

1 assignment Total 20 minutes

Week8 20 minutes

Instructor

Instructor ratings

(45 ratings)

于天立

National Taiwan University

2 Courses 31,745 learners

Offered by

National Taiwan University

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