About this course: 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
Created by: National Taiwan University
Taught by: 于天立(Tian-Li,Yu), Assistant Professor
電機工程學系(Electrical Engineering)
| Level | Beginner |
| Language | Chinese (Traditional) |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
Introduction & Intelligent agents
5 videos, 1 reading
- Video: 1-1 What is AI (i) - Acting Humanly, Thinking Humanly
- Video: 1-2 What is AI (ii) - Thinking Rationally, Acting Rationally
- Video: 1-3 AI Prehistory and History, Current AI
- Video: 1-4 Agents and Environments, Rationality, PEAS
- Video: 1-5 Environment Types, Summary
- Reading: Help us become better!
Graded: Week 1
WEEK 2
Uninformed search
6 videos
- Video: 2-1 Problem Solving Agents, Problem Formulation (i)
- Video: 2-2 Problem Formulation (ii) - Abstraction
- Video: 2-3 Search on Tree and Graph
- Video: 2-4 Uninformed Search (i) - Breadth-First Search, Uniform-Cost Search
- Video: 2-5 Uninformed Search (ii) - Depth-First Search, Depth-Limited Search, Iterative-Deepening Search
- Video: 2-6 Uninformed Search (iii) - Iterative-Deepening Search, Bidirectional Search
Graded: Week 2
WEEK 3
Informed search
6 videos
- Video: 3-1 Best-First Search (i) - Greedy Search
- Video: 3-2 Best-First Search (ii) - A* Search
- Video: 3-3 Best-First Search (iii) - Optimality of A*
- Video: 3-4 Memory Bounded Search (i) - Iterative Deepening A*, RBFS
- Video: 3-5 Memory Bounded Search (ii) - RBFS, Simplified Memory-bounded A*
- Video: 3-6 Heuristic - Preformance, Generating Heuristics
Graded: Week 3
WEEK 4
Non-classic search
7 videos
- Video: 4-1 Black-Box Optimization
- Video: 4-2 Steepest Descent
- Video: 4-3 Simulated Annealing
- Video: 4-4 Evolutionary Computation
- Video: 4-5 Non-deterministic Actions - AND-OR Search, Partial Observations (i) - Sensor-less
- Video: 4-6 Partial Observations (ii) - With Sensors
- Video: 4-7 Partial Observations (iii) - Unknown Environments
Graded: Week 4
WEEK 5
Adversarial search
6 videos
- Video: 5-1 Type of Games - Symbols, Game Tree
- Video: 5-2 Optimal Decision, Negamax Search , Alpha-Beta Pruning (i)
- Video: 5-3 Alpha-Beta Pruning (ii)
- Video: 5-4 Asperasion Windows, NegaScout
- Video: 5-5 Imperfect Decisions, Forward Pruning
- Video: 5-6 Stochastic Games, Partially Observable Games
Graded: Week 5
WEEK 6
Propositional Logic
7 videos
- Video: 6-1 Logical Agents (i) - Generic Knowledge-Based Agent, PEAS
- Video: 6-2 Logical Agents (ii) - Logic, Entailment and Models
- Video: 6-3 Propositional Logic, Inference (i) - Enumeration, Validity and Satisfiability
- Video: 6-4 Inference (ii) - Simple Knowledge, Resolution and CNF (i) - Proof by Resolution, CNF Conversion, Resolution Algorithm
- Video: 6-5 Resolution and CNF (ii) - Properties of Resolution, Ground Resolution Theorem
- Video: 6-6 Resolution and CNF (iii) - Horn and Definite Clauses, Forward Chaining
- Video: 6-7 Backward Chaining, Pros and Cons of Propositional Logic
Graded: Week 6
WEEK 7
First Order Logic
8 videos, 1 reading
- Video: 7-1 First-Order Logic (i) - Syntax of FOL and Semantics
- Video: 7-2 First-Order Logic (ii) - Using FOL, Inference (i) - Instantiation
- Video: 7-3 Inference (ii) - Propositionalization, Inference (iii) - Unification
- Video: 7-4 Inference (iii) - Unification, Inference (iv) - Forward chaining
- Video: 7-5 Inference (iv) - Forward chaining, Inference (v) - Backward chaining
- Video: 7-6 Logic Programing (i) - Prolog Systems
- Video: 7-7 Logic Programing (ii) - Redundant Inference and Infinite Loops in Prolog
- Video: 7-8 Inference (vi) - Resolution
- Reading: 問卷網址
Graded: Week 7
WEEK 8
Planning
6 videos, 1 reading
- Video: 8-1 Planning Domain Definition Language (PDDL) (i)
- Video: 8-2 Planning Domain Definition Language (PDDL) (ii)
- Video: 8-3 State-Space Search, Heuristics
- Video: 8-4 Planning Graphs
- Video: 8-5 GRAPHPLAN
- Video: 8-6 Course Review
- Reading: 臺大開放式課程（NTU OpenCourseWare）：計算機概論
Graded: Week8
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Ratings and Reviews
老师讲的很棒，例子来源于生活浅显易懂。推荐大家作为入门课程。
老師的講解非常清楚，是一堂實用的課程
He teaches a lot of search algorithms!
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赵
内容非常好，虽然后面章节有些难
遗憾的是，只讲了经典的AI，期待尽快出现代AI部分