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• Lecture Notes on Game search
• Lecture Notes on Game search

• A C program for maze search. This is a program to demonstrate mouse intelligence.

• This is a mouse intelligence program. This tries to find a Hamilton route to visit the 24 rooms on the (5, 5) floor with one square occupied by a staircase. This fails.
• Similar to the above for a (6, 6) floor. This also fails.
• This is an AI program. This tries to find a Hamilton route to visit the 24 rooms on the (5, 5) floor with one square occupied by a stair case. This program successfully declares that there is no solution.
• Similar to the above for a (6, 6) floor. This successfully finds a route.

• This solves the 8-puzzle by depth first search.

• This solves the 8-puzzle by breadth first search.

• This solves the 8-puzzle by breadth first search and reports the path to the goal. The initial configuation is different from the above example

• This solves the 8-puzzle by heuristic h(n)=W(n), where W(n) is the number of misplaced tiles.

• This illustrates alpha-beta search. Static evaluations are at the bottom of tree. 99 and -99 are to show alpha cuts and beta cuts respectively.

• This plays the tic-tac-toe game. Computer is the first player. This program searches the game tree to the bottom. It is a perfect game in the sense that if both players play carefully, the outcome is known. In this game, it is draw.

• This plays the tic-tac-toe game. Computer is the first player. This program searches the game tree to a specified level.

• This plays the Othello (Riversi) game. Computer takes the first move. Computer's pieces are "X" and yours are "O". "X" signifies black side of a piece, and "O" white. A player can overturn the pieces to his colour if he can sandwitch opponent's pieces.

• Tutorial for AI part