Nevertheless, existing calculators have a limited computation speed and, at least we don’t want to wait until the end of the Universe, we would never find it. Given its brute force nature, the algorithm could theoretically simulate all possible future moves and always find the best one. Such a solution is just one optimal solution to the problem since there may be several solutions that achieve the optimal value. Such algorithms can be useful to solve optimization problems: these kind of problems can have many possible solutions, each solution has a value, and we wish to find a solution with the optimal (minimum or maximum) value. Each node has its own value which can be both positive or negative and at the end of the search will be chosen the path with the maximum value where its value it is nothing but the sum of the values of the nodes along it. All the nodes will be visited on the current branch until all of them have been traversed after which the next path will be selected. Here, the word backtrack means that when we are moving forward and there are no more nodes along the current path, we move backwards on the same path to find nodes to traverse. In our case, a node corresponds to a different state of the environment while the depth corresponds to the maximum length of the path explored so far. It involves exhaustive searches of all the nodes of the tree by going ahead, if possible, else by backtracking. It is a recursive algorithm that uses the idea of backtracking to explore all possible paths of a tree and return the one leading to the highest reward. As already introduced earlier, our new AI consists of a deep search algorithm to exhaustively search for the best path the snake has to follow to eat its next food safe and sound.
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