8-puzzle is a very interesting and a well known problem in the field of Artificial Intelligence. It always has been an important subject in articles, books and become a part of course material in many universities. The 8-puzzle is also known as the sliding-block puzzle or tile-puzzle and is meant for a single user. 8-puzzle consists of 8 square tiles numbered 1 through 8 and one blank space on a 3 by 3 board. Moves of the puzzle are made by sliding an adjacent tile into the position occupied by the blank space, which has the effect of exchanging the positions of the tile and blank space. Only tiles that are horizontally or vertically adjacent (not diagonally adjacent) may be moved into the blank space. The objective of the game is to start from an initial configuration and end up in a configuration which the tiles are placed in ascending number order as shown in: figure 1 below.
Figure 1 Goal state of the 8-puzzle
HOW TO PLAY
The game can be played using the arrow keys. Up arrow slides a tile up into the empty space, left arrow slides a tile left into the empty space and so on. You can choose to solve it automatically by program. It will display the animation sliding the tiles and solve the 8 puzzle in least possible moves using AI.METHODOLOGY 
According to the authors  Russel  and  Norvig  in their book titled 
 Artificial Intelligence: A Modern Approach, the average solution for a 
randomly generated 8-puzzle instance is about 22 steps. This figure  is 
obtained by estimating the branching factor which is about 3 (when the 
empty tile is in the middle, there are four possible moves; when it is 
in a corner there are two; and when it is along an edge there are 
three). This means that an exhaustive search to depth 22 would look at 
about 322 ~ 3.1 x 1010 states. By keeping track of repeated states, it 
is possible to cut this down by a factor of about 170,000, because there
 are only 9!/2 = 181,440 distinct states that are reachable.ALGORITHM
After a preliminary investigation of the heuristic search strategies we 
were able to figure out that A* algorithm is the best for the 8-puzzle 
problem. A* is the most widely used form of best first search algorithm 
which is an instance of Tree-Search or Graph-Search where a best node is
 expanded on the basis of an evaluation function f(n). Here, the 
evaluation function of each node is calculated as a sum of two functions
 g(n) and h(n) where, g(n) refers to the cost to reach the node n while 
h(n) is the cost to get from node n to the goal. A* algorithm is 
both optimal and complete. It is optimal in that sense h(n) is 
admissible and is never overestimatedThe following pseudo code describes the A* algorithm:
| 
function
  A*(start,goal)  
     closedset := the empty set                 // The set of nodes
  already  evaluated.       
     openset := set containing the initial
  node // The set of tentative nodes to be evaluated.  
     g_score[start] := 0                        // Distance from
  start along optimal path.  
     h_score[start] :=
  heuristic_estimate_of_distance(start, goal)  
     f_score[start] := h_score[start]           // Estimated total distance from
  start to goal through y.  
while
  openset is not empty  
         x := the node in openset having the
  lowest f_score[] value  
         if x = goal  
             return
  reconstruct_path(came_from[goal])  
         remove x from openset  
         add x to closedset  
         foreach y in neighbor_nodes(x)  
             if y in closedset  
                 continue  
 tentative_g_score := g_score[x] +
  dist_between(x,y)  
             if y not in openset  
                 add y to openset  
                 tentative_is_better := true  
             elseif tentative_g_score <
  g_score[y]  
                 tentative_is_better := true  
             else  
                 tentative_is_better := false
   
             if tentative_is_better = true  
                 came_from[y] := x  
                 g_score[y] :=
  tentative_g_score  
                 h_score[y] :=
  heuristic_estimate_of_distance(y, goal)  
                 f_score[y] := g_score[y] +
  h_score[y]  
     return failure  
 function reconstruct_path(current_node)  
     if came_from[current_node] is set  
         p =
  reconstruct_path(came_from[current_node])  
         return (p + current_node)  
     else  
         return current_node | 
REFERENCE
1.  Rich and Knight, Artificial Intelligence.3. A* search algorithm - Wikipedia, the free encyclopedia
4. Description and a solution strategy for the 8-puzzle from http://www.8puzzle.com/
5. G. Novak, CS 381K: Heuristic Search: 8 Puzzle, 26 Sep 07
6. An appealing Java applet from www.permadi.com/java/puzzle8/
