>>> I.e. it makes the diagonal directions more important, compared to moves >>> in a straight line. >> >> I try to make that apparent in the presentation, and maybe also in the >> name I use - it creates circle-like structures on the square grid. In >> other words, increments in gridcular metric approximate increments in >> the classical Euclidean metric. At the same time, the increments provide >> quite fine granularity in the area covered, which is also useful in the >> usual application - matching of variable-sized patterns.
>But why is that better for go? Have you (or anyone) compared each way, >and this gives some quantitative improvement? >It seems to me that for variable-sized patterns that simple manhattan >distance fits go better. I can see that this metric is better than manhattan distance for connection, in that a diagonal path of the same manhattan distance as a straight path offers several different routes of the manhattan distance between the two points, where the straight path has only one, so the diagonal is more likely to make the connection than the straight. _______________________________________________ Computer-go mailing list [email protected] http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
