Minimax Algorithm

Consider a game of two players, call one of the players as MAX and the other player as MIN. And in the game MAX makes the first move and then they take turns alternatively till the end of the game.

The various components of the Game:

1. Initial State: This includes the board position and the player who will move first.
2. Successor Function: For a node it returns the list of it's successor function and the state they will result into.
3. Terminal States: The states where the game has ended.
4. Utility Function: This gives a numerical value to all the terminal states. High values are considered good for MAX and bad for MIN and vice-versa.

The following video gives a complete explanation of the Minimax Algorithm.

Following is the Minimax Algorithm:

Source: Artificial Intelligence: A Modern Approach

ai-class, ml-class and db-class

I enrolled in all three courses of Stanford which were a part of a new online initiative by them, and today when I saw the lectures and worked on the quizzes I realize how exciting the courses are. Firstly you can watch the lectures whenever you want and wherever you want + you can watch them again and again until you get the concept completely and lastly I like the concept of me choosing to take the course rather that it being thrust upon me which happens in almost all universities in India. 

There are three courses which are being offered and I have opted to take all of them and they are pretty interesting!

1. Introduction to Artificial Intelligence (http://www.ai-class.com)
2. Introduction to Databases (http://www.db-class.org)
3. Machine Learning (http://www.ml-class.org)

I hope I will have a good time and will learn a lot and I am happy that some initiatives are being taken towards Online Education. I myself took up a small initiative sometime during the start of this year. Here is the link http://www.unacademy.in