際際滷

際際滷Share a Scribd company logo

Artificial intelligence1

Download as PPT, PDF
Y
yosser atassi

This document outlines the syllabus for an Artificial Intelligence course taught by Dr. Yosser ATASSI, including an introduction to AI, problem solving techniques like search and constraint satisfaction, knowledge representation, machine learning including neural networks, and different approaches to AI such as learning, rule-based systems, search, planning, and robotics. The textbook for the course is "Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig. The course will cover topics in intelligent agents, logical reasoning, inference, and knowledge representation.

1 of 23
Downloaded 11 times
AI Dr. Yosser ATASSI 1 Artificial Intelligence Lecture 1 Dr. Yosser ATASSI
AI Dr. Yosser ATASSI 2 Textbook: Stuart Russell & Peter Norvig " Artificial Intelligence: A Modern Approach" Prentice Hall Series in Artificial Intelligence.
AI Dr. Yosser ATASSI 3 Syllabus I Artificial Intelligence 1 Introduction 2 Intelligent Agents II Problem-solving 3 Solving Problems by Searching 4.Informed Search and Exploration 5.Constraint Satisfaction Problems 6. Adversarial Search III Knowledge and reasoning 7. Logical Agents 8. First-Order Logic 9. Inference in First-Order Logic 10. Knowledge Representation
AI Dr. Yosser ATASSI 4 IV Machine learning IV Machine learning Two layer artificial neural networks 1. Biological motivation; 2. ANN representation; 3. Perceptrons; 4. Worked example; 5. The learning abilities of perceptrons; Multi-layer artificial neural networks 1. Architectures; 2. Backpropagation; 3. Worked example; 4. Avoiding local minima; 5. Overfitting considerations; 6. Appropriate problems for ANNs;
AI Dr. Yosser ATASSI 5 Introduction What is AI AI history Approaches to AI
AI Dr. Yosser ATASSI 6
AI Dr. Yosser ATASSI 7
AI Dr. Yosser ATASSI 8
AI Dr. Yosser ATASSI 9
AI Dr. Yosser ATASSI 10
AI Dr. Yosser ATASSI 11
AI Dr. Yosser ATASSI 12
AI Dr. Yosser ATASSI 13
AI Dr. Yosser ATASSI 14 Approaches to AI Learning Rule-Based Systems Search Planning Ability-Based Areas Robotics Agents
AI Dr. Yosser ATASSI 15 Learning Explanation Discovery Data Mining No Explanation Neural Nets Case Based Reasoning
AI Dr. Yosser ATASSI 16 Learning: Explanation
AI Dr. Yosser ATASSI 17 Learning: No Explanation Neural nets
AI Dr. Yosser ATASSI 18 Rule-Based Systems Logic Languages Prolog, Lisp Knowledge bases Inference engines
AI Dr. Yosser ATASSI 19 Rule-Based Languages: Prolog Father(abraham, isaac). Male(isaac). Father(haran, lot). Male(lot). Father(haran, milcah). Female(milcah). Father(haran, yiscah). Female(yiscah). Son(X,Y) Father(Y,X), Male(X). Daughter(X,Y) Father(Y,X), Female(X). Son(lot, haran)?
AI Dr. Yosser ATASSI 20 Rule Based Systems KRS
AI Dr. Yosser ATASSI 21 Search All AI is search Game theory Problem spaces Every problem is a virtual tree of all possible (successful or unsuccessful) solutions. The trick is to find an efficient search strategy.
AI Dr. Yosser ATASSI 22 Search: Game Theory 9!+1 = 362,880
AI Dr. Yosser ATASSI 23 Natural Language Recognition You give me the gold pronoun n verb pronoun d article noun VP NP VP NP VP NP sentence w PERSON: Joe PERSON: FredTRANSACTION GOLD: X REPT OBJ AGNT Audio Words Syntax Context Semantics

More Related Content

Artificial intelligence1

  • 1. AI Dr. Yosser ATASSI 1 Artificial Intelligence Lecture 1 Dr. Yosser ATASSI
  • 2. AI Dr. Yosser ATASSI 2 Textbook: Stuart Russell & Peter Norvig " Artificial Intelligence: A Modern Approach" Prentice Hall Series in Artificial Intelligence.
  • 3. AI Dr. Yosser ATASSI 3 Syllabus I Artificial Intelligence 1 Introduction 2 Intelligent Agents II Problem-solving 3 Solving Problems by Searching 4.Informed Search and Exploration 5.Constraint Satisfaction Problems 6. Adversarial Search III Knowledge and reasoning 7. Logical Agents 8. First-Order Logic 9. Inference in First-Order Logic 10. Knowledge Representation
  • 4. AI Dr. Yosser ATASSI 4 IV Machine learning IV Machine learning Two layer artificial neural networks 1. Biological motivation; 2. ANN representation; 3. Perceptrons; 4. Worked example; 5. The learning abilities of perceptrons; Multi-layer artificial neural networks 1. Architectures; 2. Backpropagation; 3. Worked example; 4. Avoiding local minima; 5. Overfitting considerations; 6. Appropriate problems for ANNs;
  • 5. AI Dr. Yosser ATASSI 5 Introduction What is AI AI history Approaches to AI
  • 6. AI Dr. Yosser ATASSI 6
  • 7. AI Dr. Yosser ATASSI 7
  • 8. AI Dr. Yosser ATASSI 8
  • 9. AI Dr. Yosser ATASSI 9
  • 10. AI Dr. Yosser ATASSI 10
  • 11. AI Dr. Yosser ATASSI 11
  • 12. AI Dr. Yosser ATASSI 12
  • 13. AI Dr. Yosser ATASSI 13
  • 14. AI Dr. Yosser ATASSI 14 Approaches to AI Learning Rule-Based Systems Search Planning Ability-Based Areas Robotics Agents
  • 15. AI Dr. Yosser ATASSI 15 Learning Explanation Discovery Data Mining No Explanation Neural Nets Case Based Reasoning
  • 16. AI Dr. Yosser ATASSI 16 Learning: Explanation
  • 17. AI Dr. Yosser ATASSI 17 Learning: No Explanation Neural nets
  • 18. AI Dr. Yosser ATASSI 18 Rule-Based Systems Logic Languages Prolog, Lisp Knowledge bases Inference engines
  • 19. AI Dr. Yosser ATASSI 19 Rule-Based Languages: Prolog Father(abraham, isaac). Male(isaac). Father(haran, lot). Male(lot). Father(haran, milcah). Female(milcah). Father(haran, yiscah). Female(yiscah). Son(X,Y) Father(Y,X), Male(X). Daughter(X,Y) Father(Y,X), Female(X). Son(lot, haran)?
  • 20. AI Dr. Yosser ATASSI 20 Rule Based Systems KRS
  • 21. AI Dr. Yosser ATASSI 21 Search All AI is search Game theory Problem spaces Every problem is a virtual tree of all possible (successful or unsuccessful) solutions. The trick is to find an efficient search strategy.
  • 22. AI Dr. Yosser ATASSI 22 Search: Game Theory 9!+1 = 362,880
  • 23. AI Dr. Yosser ATASSI 23 Natural Language Recognition You give me the gold pronoun n verb pronoun d article noun VP NP VP NP VP NP sentence w PERSON: Joe PERSON: FredTRANSACTION GOLD: X REPT OBJ AGNT Audio Words Syntax Context Semantics