The document discusses various search techniques in artificial intelligence, including informed and uninformed search strategies. It covers algorithms like breadth-first search (BFS), depth-first search (DFS), hill climbing, and A* search, highlighting their properties, time complexities, and methods for generating and testing solutions. Additionally, it emphasizes the comparison of these techniques in solving problems effectively.

1. ARTIFICIAL INTELLIGENCE
PANKAJ DEBBARMA
Deptt. of CSE, TIT, Narsingarh
Informed Search

2. CONTENTS
Search
Techniques
• Search Techniques
• Uninformed Search
• Informed Search
• Generate and Test
• Hill Climbing
• Best First Search
• A* Search

3. Constraint
Satisfaction
Means-end
Analysis
AO* Search
A* Search
Informed Search
Search Techniques
Uninformed Search
Generate and Test Hill Climbing
Breadth First
Search
Cost First
Search
Depth Limited
Search
Depth First
Search
Iterative
Deepening DFS
Problem
Reduction
Best First
Search

4. Breadth-first search (BFS)
• Uninformed
• FIFO (Queue data
structure)
• Shallowest node
• Complete
• Optimal
• Time Complexity
– O(V+E)
– O(bd)
A
F
D
C
E
B
G
N
J
H I
M
K L
0
2
1
4
3

5. Depth-first search (DFS)
• Uninformed
• LIFO (Stack data
structure)
• Deepest node
• Incomplete
• Non-optimal
• Time Complexity
– O(V+E)
– O(bd)
A
F
D
C
E
B
G
N
J
H I
M
K L
0
2
1
4
3

6. Iterative Deepening DFS
A
F
D
C
E
B
G
N
J
H I
M
K L
d = 0
d = 1
d = 3
d = 2
d = 4

7. Cost first search
Note visited:
A, C, B, D, G, E, L,
I, K, H, F, J, M, N
A
F
D
C
E
B
G
N
J
H I
M
K L
4
6
3
4
3
4
3
2
7
2
3
6
1
Child B C D G H E F I L J K M N
Cost 4 3 7 7 10 7 10 9 8 11 9 12 12

8. Algorithm
1. Generate all possible
solution.
2. Test to see if this is the
expected solution.
3. If the solution has been
found quit else go to step 1.
Generate and test

9. Generate and test

10. • Find high points in a
fitness landscape
• Local search algorithm
• Greedy approach
• No backtracking
Hill Climbing

11. Best First Search

12. Best First Search
A
C G
B
D
S

13. • Combines the cost so far and the estimated
cost to the goal
• This gives us an estimated cost of the
cheapest solution through n
A* Search

14. A* Search

15. A* Search