Storm Blueprints: Patterns for Distributed Real-time Computation by 未知

Author:未知
Language: eng
Format: epub
Publisher: Packt Publishing

Tip

The Negamax algorithm accomplishes the same more succinctly by alternating the sign of the score. Additionally, in a real-world scenario, we might apply Alpha-Beta pruning, which attempts to trim the branches of the tree that are explored. The algorithm only considers branches that fall within a threshold. In our use case, this is not necessary because the search space is small enough to explore in its entirety.

In our simple use case, it is possible to enumerate the entire game tree. In more complicated games such as Chess, the game tree is impossible to enumerate. In an extreme case such as Go, experts have calculated the number of legal boards to be in excess of 2 x 10170.

The goal of the Minimax algorithm is to traverse the game tree and assign a score to each node. In our Storm topology, which is not beholden to any SLA, the score of any non-leaf node is simply the maximum (or minimum) of its descendants. For a leaf node, we must interpret the game state into a corresponding score. In our simple use case, there are three possible outcomes: we win, our opponent wins, or the game is a tie.

In our synchronous system, however, we might very well run out of time before we reach a leaf node. In this case, we need to calculate the score from the current state of the board. Scoring heuristics are often the most difficult aspect of developing an AI application.

For our simple use case, we will compute the score for any board by considering the lines in the grid. There are eight lines to consider: three horizontal, three vertical, and two diagonals. Each line contributes to the score according to the following table:

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