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🝔 Remove Highest Score

Removes edges with the highest heuristic scores

Table of content

This refinement removes a single connected edge for each point for each point: the one with the highest score based on connected 🝰 Heuristics.

Note that the removed Edge can be the same for multiple, different Vtx.

Not all heuristics can be yield usable scores outside of a search context. For example, 🝰 Azimuth and 🝰 Inertia require clear seed/goals and search history to assign a given score. Such heuristics will yield a default score based on their own settings.

details/edges-refine/refine-remove-highest-score.png

Available Heuristics Modules


🝰 Heuristic Attribute

Attribute-driven heuristics

The Attribute heuristics uses custom point or edge value as raw score.

🝰 Shortest Distance

Favor shortest distance.

The Shortest Distance heuristic node …

🝰 Feedback

Favor uncharted points & edges.

The Feedback heuristic add/remove score value to points & edges that are “in use” by other previously computed paths.

🝰 Inertia

Favor active direction preservation.

The Inertia heuristic uses the ongoing traversal data to try and maintain a consistent direction, as if the algorithm had “inertia”.

🝰 Steepness

Favor flat trajectories.

The Steepness heuristic uses the edge angle against an up vector to compute a dot product that is used to determine whether the edge should be considered flat or not.

🝰 Azimuth

Favor edges directed toward the goal.

The Azimuth heuristic attempt to force the path to always aim toward the goal.

🝰 Least Nodes

Favor traversing the least amount of nodes.

The Least Nodes heuristic favor node count traversal over anything else.