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Strategy.txt
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Strategy.txt
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•Utility score based on a heuristic:
For every move that is made by either player, we will be calculating a
heuristic score for that move to determine how effective the move is and
will improve the chances of winning for the player. In this approach,
each heuristic is assigned a utility score that can either increase as a
rewarding mechanism after an improving move or decrease as a punishment
mechanism after a worsening move. The utility score is updated after each
step of the algorithm, and the heuristic with the best score can be selected
as the default strategy.
•Minmax with alpha-beta pruning:
Every move of a player will lead to a game state which will be advantageous
to one and disadvantageous for another player. The first player will try to
maximize the heuristic score, and is called the MAX player, while the second player,
the MIN player, tries to minimize the heuristic score. The algorithm will recursively
alternate between the MAX player and the MIN player until it reaches a terminal node.
The game tree will be searched in a depth-first way meaning that the algorithm will
search the deepest unvisited branch until a terminal node is reached. The value of the
terminal node is then returned to the parent node. When all the branches of a node
have been visited, the player can now choose the best branch from that node and return
the value of that branch to the parent node again up to the root node.