Building Universes from Code: How Algorithms Learn to Walk

How algorithms learn to walk...

Our universe is built from atoms and molecules, governed by the quiet laws of physics. A mountain stands because gravity demands it. A valley forms because water insists on finding its way.

But in a game world, none of that exists - not until we create it. A mountain is just geometry; a field is only an arrangement of vertices and pixels. There is no gravity, no friction, no path - unless we teach the world to understand itself.

So, the question is how do we replicate the magical simplicity of objects moving in the real world into our game world?

The essence is we need a mapping algorithm that can identify walkable areas in a game level.  It means building an artificial intuition for what it means to stand, to move, to explore.

Through raycasting, spatial analysis, and pathfinding, we give structure to chaos - we define the invisible laws that allow non-player characters to navigate their universe as we navigate ours.

It’s a reminder that whether our worlds are made of atoms or polygons, the challenge is the same: to make sense of space, and to find our path through it.

The conundrum facing developers today is how precisely do you do it? Follow and I will tell you in the next post how we’re making Baldr Engine do this.

Tim Ellis

5th November 2025