----------------------------------- Module Description -----------------------------------
{-WETT
  The basic idea behind the AI algorithm is that it works with the minimax technique
  The minimax technique relies on the conceptually simple idea of game trees.
  A game tree is an expansion of the total state space of a game. Each node of the
  tree contains the complete description of one state of the game.
  The minMaxTree function traverses recursively n steps down the game tree and simulates all possible
  moves within this path down to the bottom. As more moves are possible as longer 
  takes the program execution, that's why I have restricted the traversing to four steps.
  Suppose I would like to use it to play a game as the first player. Since I am the first player, 
  I'm the maximizing player. The ultimate goal is to find which of the children of the root 
  yields the highest score. To compute this, we consider each of the children individually, 
  and apply the minimax procedure to them one-by-one. However, since we are now on the second 
  level, we must play the part of the minimizing player, whose turn it now is. 
  Therefore, we try to find the node that yields the lowest score. 
  We continue this way down the tree, alternating between maximizing and minimising, 
  until we reach the bottom. The scores are then propagated up through the tree until we 
  get back to the root. Now, the score of each child is known, and we can choose the best move: 
  the greatest if we are the maximizing player, or the least if we are the minimizing. 
  Between each iteration I add the value of the advantage function which calculates
  the mobility of the player and the pice difference.
  Furthermore I add to each value the heuristic weight that has been determined 
  experimentally and base on the advantage you gain when you occupy one of the 
  squares. For example corners are very popular because they're secure and cannot be
  got lost once you've gained them. That's why corners does have a higher weight than 
  all the other squares. Through this concept it is guaranteed that we can make a good
  decision although we don't traverse through the entire games tree to find the 
  globally best solution.
  source: http://www.mkorman.org/othello.pdf
-}