HeuristicsA single heuristics definition
Table of content
Heuristics Attribute allows fine-grained and precise control over pathfinding constraints by leveraging user-defined attributes.
When dealing with values, keep in mind that lower numbers are considered more desirable by the
⊚ Search algorithms.
Properties
| Property | Description |
|---|---|
| Basics | |
| Weight Factor | Weight of this heuristic against other concurrent heuristics. The higher the value, the more important it is during resolution. |
| Invert | Whether the score of this heuristic should be inverted. This effectively samples the score curve backwards. |
| Score Curve | Curve over which the heuristic values will be remapped. |
| Attribute Settings | |
| Source | Whether to read the attribute from Vtx or Edges
|
| Attribute | The attribute that will be used as score. |
| Local Weight | |
| Use Local Weight Multiplier | If enabled, this heuristic will be using a dynamic, per-point weight factor. |
| Local Weight Multiplier Source | Whether to read the weight from Vtx or Edges points. |
| Local Weight Multiplier Attribute | Attribute to read the local weight from. |
| Roaming | |
| UVW Seed | Bounds-relative roaming seed point |
| UVW Goal | Bounds-relative roaming goal point |
Roaming seed/goal points are used as fallback in contexts that are using heuristics but don’t have explicit seed/goals; such as Cluster Refine‘MST or Score-based refinements.