À propos de ce cours : 本課程有兩大課程目標： 1. 使同學了解如何以搜尋達成人工智慧 2. 使同學能將相關技術應用到自己的問題上
Créé par : National Taiwan University
Enseigné par : 于天立(Tian-Li,Yu), 副教授（Associate Professor）
電機工程學系(Electrical Engineering)
| Niveau | Beginner |
| Langue | Chinese (Traditional) |
| Comment réussir | Réussissez tous les devoirs notés pour terminer le cours. |
| Notes des utilisateurs |
Programme de cours
SEMAINE 1
Introduction & Intelligent agents
5 vidéos, 1 lecture
- Vidéo: 1-2 What is AI (ii) - Thinking Rationally, Acting Rationally
- Vidéo: 1-3 AI Prehistory and History, Current AI
- Vidéo: 1-4 Agents and Environments, Rationality, PEAS
- Vidéo: 1-5 Environment Types, Summary
- Reading: Help us become better!
Noté: Week 1
SEMAINE 2
Uninformed search
6 vidéos
- Vidéo: 2-2 Problem Formulation (ii) - Abstraction
- Vidéo: 2-3 Search on Tree and Graph
- Vidéo: 2-4 Uninformed Search (i) - Breadth-First Search, Uniform-Cost Search
- Vidéo: 2-5 Uninformed Search (ii) - Depth-First Search, Depth-Limited Search, Iterative-Deepening Search
- Vidéo: 2-6 Uninformed Search (iii) - Iterative-Deepening Search, Bidirectional Search
Noté: Week 2
SEMAINE 3
Informed search
6 vidéos
- Vidéo: 3-2 Best-First Search (ii) - A* Search
- Vidéo: 3-3 Best-First Search (iii) - Optimality of A*
- Vidéo: 3-4 Memory Bounded Search (i) - Iterative Deepening A*, RBFS
- Vidéo: 3-5 Memory Bounded Search (ii) - RBFS, Simplified Memory-bounded A*
- Vidéo: 3-6 Heuristic - Preformance, Generating Heuristics
Noté: Week 3
SEMAINE 4
Non-classic search
7 vidéos
- Vidéo: 4-2 Steepest Descent
- Vidéo: 4-3 Simulated Annealing
- Vidéo: 4-4 Evolutionary Computation
- Vidéo: 4-5 Non-deterministic Actions - AND-OR Search, Partial Observations (i) - Sensor-less
- Vidéo: 4-6 Partial Observations (ii) - With Sensors
- Vidéo: 4-7 Partial Observations (iii) - Unknown Environments
Noté: Week 4
SEMAINE 5
Adversarial search
6 vidéos
- Vidéo: 5-2 Optimal Decision, Negamax Search , Alpha-Beta Pruning (i)
- Vidéo: 5-3 Alpha-Beta Pruning (ii)
- Vidéo: 5-4 Asperasion Windows, NegaScout
- Vidéo: 5-5 Imperfect Decisions, Forward Pruning
- Vidéo: 5-6 Stochastic Games, Partially Observable Games
Noté: Week 5
SEMAINE 6
Propositional Logic
7 vidéos
- Vidéo: 6-2 Logical Agents (ii) - Logic, Entailment and Models
- Vidéo: 6-3 Propositional Logic, Inference (i) - Enumeration, Validity and Satisfiability
- Vidéo: 6-4 Inference (ii) - Simple Knowledge, Resolution and CNF (i) - Proof by Resolution, CNF Conversion, Resolution Algorithm
- Vidéo: 6-5 Resolution and CNF (ii) - Properties of Resolution, Ground Resolution Theorem
- Vidéo: 6-6 Resolution and CNF (iii) - Horn and Definite Clauses, Forward Chaining
- Vidéo: 6-7 Backward Chaining, Pros and Cons of Propositional Logic
Noté: Week 6
SEMAINE 7
First Order Logic
8 vidéos, 1 lecture
- Vidéo: 7-2 First-Order Logic (ii) - Using FOL, Inference (i) - Instantiation
- Vidéo: 7-3 Inference (ii) - Propositionalization, Inference (iii) - Unification
- Vidéo: 7-4 Inference (iii) - Unification, Inference (iv) - Forward chaining
- Vidéo: 7-5 Inference (iv) - Forward chaining, Inference (v) - Backward chaining
- Vidéo: 7-6 Logic Programing (i) - Prolog Systems
- Vidéo: 7-7 Logic Programing (ii) - Redundant Inference and Infinite Loops in Prolog
- Vidéo: 7-8 Inference (vi) - Resolution
- Reading: 問卷網址
Noté: Week 7
SEMAINE 8
Planning
6 vidéos, 1 lecture
- Vidéo: 8-2 Planning Domain Definition Language (PDDL) (ii)
- Vidéo: 8-3 State-Space Search, Heuristics
- Vidéo: 8-4 Planning Graphs
- Vidéo: 8-5 GRAPHPLAN
- Vidéo: 8-6 Course Review
- Reading: 臺大開放式課程（NTU OpenCourseWare）：計算機概論
Noté: Week8
FAQ
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Créateurs
National Taiwan University
We firmly believe that open access to learning is a powerful socioeconomic equalizer. NTU is especially delighted to join other world-class universities on Coursera and to offer quality university courses to the Chinese-speaking population. We hope to transform the rich rewards of learning from a limited commodity to an experience available to all.More courses information, the official Facebook Page: https://www.facebook.com/ntumooc2017/
Notation et examens
For the most AI online courses, they usually tech you how to use the tool and build up into your system. insted of them, this course talk about the from AI concept and therory. For my preseonal, I like this like course than "how to use" course. It is a base, so that we can have a theory backgoud to support more advanced topic and build up our AI system. Besides, teacher always use a simple example to show the "what algorithm is" it makes us very easy to understand that. For example, I knew A* manay years ago but can not understand what is heristic h and he use a MRT as an example, then I finallly understand it. I'd recommend guys to choice the course if he/she wants to learn the AI
THIS COURSE REALLY SAVE ME , FROM NCKU STUDENT
总体不错，传统AI介绍的比较多，最好加上编程题。
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