Introduction to A * pathfinding algorithm (iv)

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Path scoring

We will give each square a score of G + H:

• G is the move cost from the start point A to the current block. So for a neighbor block that starts at point A, the value is 1, but the farther away from the start point, the greater the value.
• H is the current block to the destination block (we call this point as a point with a bone b!) Estimated move cost, which is often called heuristic algorithm, because we don't really know how much it costs-it's just an estimate.

You may be surprised by the meaning of "mobile spending". In this game it is very simple-the number of blocks (via).

In any case, remember that you can make our game different. For example:

• If you allow diagonal movement, you may set the cost of the diagonal move a bit higher.
• If you have different terrains, you may be able to set them differently by spending them--for a chestnut: swamp, water or a poster of a cat girl;-)

That's the general idea-now we'll look further at how to calculate the values of G and H.

More about G

Recall that G is the cost of moving from the start point A to the current block (in this game, the number of blocks passed).

To calculate g, we need to take out the g of its parent square (which represents where we came from) and add 1. Therefore, the G value of each block represents the total cost from point A to the general path of its own block.

With a chestnut, a piece shows 2 different paths to 2 different bones, and the G value of each block is listed in the BLOCK:

More about H

Recall the following, H is the estimated mobile cost of the current block to the destination (in our game, that is, the number of squares passing through).

It is estimated that the closer the move is to the actual cost, the more accurate the final path will be. If the estimate is biased, the resulting path will not be the shortest (but may still be close). This topic is a bit complicated, so we won't go into the details in this series, but I'll provide a link to the article at the end. It explains very well.

In short, we will use the "Manhattan Distance Approach" (also known as "Manhattan Length" or "Block Distance"), which only calculates the number of squares that reach the horizontal and vertical point B, but does not take into account any obstructions or different terrains.

For a chestnut, here is a picture showing the use of "block distance" to estimate the H value from a different starting position to a destination (shown in an empty space):

Introduction to A * pathfinding algorithm (iv)