ARTIFICIAL INTELLIGENCE FULL NOTES FOR UNIVERSITY AND ENTRANCE LEVEL EXAM
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IN THESE DOCUMENT YOU WILL GET TO KNOW ABOUT ARTIFICIAL INTELLIGENCE AND CAN PREPARE FOR YOUR EXAM THROUGH NOTES IN THESE DOCUMENT YOU WILL GET TO KNOW ABOUT What is State Space Search, Uninformed Vs Informed Search, Breadth search technique in artificial intelligence, Depth First Search (DFS), Bid...
What is State Space Search | Introduction to Problem Solving in
Artificial Intelligence
State space searching It is one of the major application of artificial
intelligence. Problem solving That is how to solve a particular problem
And if we talk about era of 1960-1970 At that time the major research
that was done in artificial intelligence That is done on problem solving
And in which we talk related to game Like tic tac toe game is there. In 8
puzzle problem that we have a board of 3 * 3, we have 9 spaces and 9
places In which we have 8 tiles which are numbered. I have random tiles
numberd 1,2,3,4,5,6,7,8 I have numbered tiles And I have one empty space
Now over here first of all I have to represent the problem precisely That
I have. I know that this is my start state Now I want goal state Where I
want to reach Otherwise you will keep on searching. You are starting to
explore your searching And these are different branches These different
branches are getting formed. If we keep the space on left side Then this
will be formed over here like this If I do it on left then 5 will come
here. If you move it left side then the next state That will be one of my
resultant state Then comes cost We measure it in cost What is the meaning
of cost?
We do searching in 2 ways either we do it uninformed or blind search. In
uninformed search we use concept of heuristic due to which we try to
solve the problem quickly In which we go towards benefit towards local
benefit So that my problem can get solved quickly Because uninformed
takes exponential time Because in uninformed B^d Time complexity is O
( b^d ).
Uninformed Vs Informed Search in Artificial Intelligence with Example
Difference between uninformed and informed searching. In informed
searching we are using information And we tell that information Heuristic
This is very important point I will explain you with a simple example Let
's say travelling salesman problem If we talk about TSP problem there
will be ( n-1 ) ! Possibilities How much will be a searching space (n-1)
If you have 5 number of cities That is value of n Then (5-1 - 4) ! That
is 4 ! We generally call as NP problem NP problem, which means non
polynomial problem. To solve non polynomial problem, we use heuristic
method. Heuristic method helps you like in travelling salesman problem.
In 24 puzzle problem you might have to go up to 10^24 states which is
practically impossible A very big value. Depth first search is time
consuming and this is a quick solution Hand over here if we talk about
the real life example Or if I talk on its bases Which are the popular
algorithms that is depth first search Breadth first search. In informed A
* algorithm is very important Heuristic DFS is there Or heuristic BFS can
also be there Best first search method is there.
Breadth search technique in artificial intelligence.
Breadth search technique in artificial intelligence. In this video we
discuss all the key points and important points regarding it regarding
it. These all points will be very much helpful to you even if you are
studying artificial intelligence in university or college level exam. A
is taking us ahead at how many places From A where all we can go ? First
, we have added those elements over here So which are the elements ? B , C
and D You can write this in any order It is not necessary that you write
B. C can take us to G and H So we inserted G & H from tail So in this way
we just have to keep on going Then we removed D from here The meaning of
removing D is Where is D taking us It is taking them on I. This knowledge
is the most important key point In BFS And this is only asked the most.
level. level That means instead of going in deep It completes the
shallowest node the nearest node. In this will move ahead level wise
level wise. level that means. Instead of going deep, it completes
shallowest nodes the nearest nodes. level and moves level by level only.
Instead of DFS we talk about BFS Breadth First Search It is completing
all the levels one by one in this way Then definitely it will give answer
That is why we tell this over here Complete What is the meaning of
complete This will definitely give an answer It is not incomplete That
means if you search any element Even if you are searching G So to search
G you will go in this only As you got G element Let 's say over here you
had found G element. Depth Depth means If we talk on each particular node
3 elements We have 3 children We have value of b as 3 And see what is
depth We have depth as 2 Then see 3^2 means 9 When we are searching this
element , G Then we will not need more then 9 search. If we consider that
there will not be more then 3 children Then 3 and 3 is 6 And 3 is 9 That
means we will get result in 9 search That 's why it power O ( b^d )
Depth First Search (DFS) with example | Uninformed Search | Artificial
Intelligence
DFS that is Depth First Search algorithm in artificial intelligence. In
this video you will come to know about all the important points and
keyword about DFS. In competitive exams like NTA NET or even if you
preparing for college or university level exam For artificial
intelligence Then all the points will be clear over here. DFS sequence is
one of the possible DFS sequences you can follow in anyway. If we talk in
this from A either I can put B & C first In this way you can following
any Let 's say if I follow this Then last in first out So which was last
in C , that means we pushed C in the last So we 'll pop C only So over
here after A where am I going I am going on C That means I went in this
direction Now after C Look carefully over here From C I can go to F & G
Again. BFS will always give optimal result only If all the cost are
similar We are talking just about that If cost of each node is different
Of each edges Then we do not use BFS We use the heuristic method Like A *
But if we talk about DFS Then it is not necessary that DFS will give us
an optimal solution It is possible that the solution which it is giving
me is not optimal.
In binary tree 2 children are possible In ternary 3 are possible But over
here any number of children can be possible According to that we have O (
b^d ) called the branching factor. In 4 searches only it can make us
reach to the goal state It is only when the cost of each edge we consider
it as similar.
Bidirectional Search Algorithm in Artificial Intelligence in Hindi with
Real Life Examples
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