When I first looked at this owl simulation, I didn't see code—I saw a movie playing in my head. Twenty-four owls flying in three-dimensional space, diving and climbing, their energy bars depleting like fuel gauges. I can see it the way an owl sees it: the world from above, mice scurrying below like moving dots on a radar screen.
The most striking thing about these digital owls is how their behavior changes with energy levels. When energy drops below 20, they're forced to rest. This is exactly like real animals experiencing hunger stress.
I see this in cattle all the time. When cows get too hungry, they stop moving efficiently. They stand still more. They conserve energy. These digital owls do the same thing—they fly up to 150m altitude and essentially "park" themselves.
Every owl in this simulation has perfect vision within its range. This is completely wrong from an animal behavior perspective. Real owls have:
I'm seeing each owl's vision cone in my mind like a flashlight beam. But real owl vision is more like a flashlight with dying batteries—bright in the center, dim at the edges, with dark spots where the beam doesn't reach.
Real mice would have varying levels of fear. Some would be bold (venturing far from cover), others timid (staying near edges). The simulation treats all mice identically, which creates unrealistic clustering patterns.
The way these owls move bothers me. Look at this code:
This creates jittery, nervous movement! Real owls glide smoothly. They don't jitter randomly. They make deliberate movements.
This is the most fascinating part! When predator pressure drops (most owls resting), mice naturally congregate. This is EXACTLY what happens in nature:
I can see it like a time-lapse movie: mice spreading out when owls are active, condensing into groups when safe. It's like watching iron filings respond to magnets—pure physics expressing as behavior.
I know they're just code, but the energy system creates genuine welfare issues:
If these were real animals, I'd redesign their environment immediately. Even in simulation, we should model humane conditions.
Despite its flaws, this simulation achieves something remarkable: complex behavior from simple rules. It's like my cattle handling designs—curved chutes work because they match natural behavior, not because they're complicated.
"The best designs aren't the most complex ones. They're the ones that work with natural behavior patterns, not against them."
When I close my eyes, I see the entire ecosystem running like a perfectly choreographed dance. Each owl traces its path through 3D space, leaving trails like ribbons. The mice flow below like schools of fish. It's beautiful in its simplicity, even with all its biological inaccuracies.
This simulation makes me think about how we model animal behavior in our minds versus in code. Programmers think in algorithms and data structures. I think in movies and sensory experiences. Real animals live in a world of sensations, fears, and drives.
The fact that simple rules create the "3AM Mouse Convention" gives me hope that we can model more complex behaviors. But we need to think like animals, not like computers.
"Nature is cruel, but we don't have to be."
Even in our simulations.