#2.1 What is AI? #2.2 Omniscience, Learning, and autonomy #2.3 Properties of task Environments #2.4 Agent Functions and Program #2.5 Types of Agent programs

#3.1 Problem solving #3.2 The Vacuum World #3.3 Search Algorithms #3.4 Breadth-First Search #3.5 DFS Search Tree #3.6 Evaluation of Search Algorithms #3.7 DFS with a depth-limit L #3.8 Iterative Deepening Search (IDS) #3.9 Informed search algorithms #3.10 Greedy Search #3.11 A * #3.12 Greedy -part2 #3.13 A* -part2

#4.1 Logical Agents #4.2 Logic in general #4.3 Truth tables for connectives #4.4 First-order logic #4.5 Equality

#5.1 History of Robotics #5.2 General Framework of Robotics

#6.1 Introduction to Computer Vision

#7.1 task Environment #7.2 أختياري-mid #7.3 8-puzzle #7.4 Iterative Deepening Search (IDS) #7.5 Search Algorithms #7.6 Bidirectional Search #7.7 EXERCISE - FOL #7.8 EXERCISE - FOL #7.9 A start #7.10 admissible #7.11 Greedy Search #7.12 Truth tables #7.13 EXERCISE - FOL #7.14 EXERCISE - FOL #7.15 Breath First Search (BFS) #7.16 Forward Propagation Example

#8.1 EXERCISE1-3 #8.2 EXERCISE - 4 #8.3 EXERCISE - 5

#9.1 Techniques to make Learn for an agent #9.2 Artificial Neural Networks #9.3 Standard structure of an artificial neural network