Algobox - Hunter Prey Dynamic Equilibrium v1.1

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Hunter Prey Dynamic Equilibrium v1.1

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Author: T_Reißig

Group: Educational

Filesize: 447.56 kB

Date added: 2025-12-29

Rating: 5.6

Downloads: 565

Comments: 4

Ratings: 2

Times favored: 0

Made with: Algodoo v2.2.4

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Edit:
- slight changes to the code to increase performance. This allows the "law of big numbers" to take effect. The resulting graphs are much closer to the differential equations and much more consistent over time. You can play the simulation at up to 4x sim speed to get results faster.

Content
This simulation aims to recreate the dynamic equilibrium of the "Lotka-Volterra-equations". Those represent the influence the population of a hunter animal has on the reproduction rate of its prey animal and vice versa.
Here the hunters are represented as red circles (as soon as the sim starts) and their prey are yellow dots. When colliding yellow dots will turn into red circles, representing the idea, that the hunter successfully fed itself and its offspring. Failing to eat will result in death for the hunters. Prey dots will eventually reproduce unless eaten. The green patches are safe zones for prey animals which cannot be entered by hunters.
Currently the dynamic equillibrium will be maintained for about 3-10 minutes. Eventually either all prey gets eaten and the hunters die out shortly after, or (more likely) the hunters die out and prey will reproduce exponantially and indefinitely.

You can change the odds of those events and the time of their occourence by...
... changing the location, size and amount of Objects (green bushes/trees)
... changing the location, size and amount of safe zones (green patches)
... changing the time it takes to starve to death for hunters or reproducing for prey
--> right-click on one of the black dots before starting --> script menu --> onSpawn: change the variables or their randomness factor then save and restart the simulation for it to be applied.

Have fun and let me know if you can optimize the variables for a higher duration and better results!

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Xray

2026/02/14 00:05:54

While watching the simulation, it occurred to me that the hunter/prey interaction is purely by chance. But in the real world, hunters don't randomly and accidentally bump into prey animals and then eat them. A predator who was recently fed will ignore prey animals, even ones that are close to them. After a while, the predator will become hungry and then will start to think about seeking and killing a prey animal. This simulation doesn't seem to operate like that. It is purely by chance that a predator eats a prey animal. Even when predator and prey animals happen to be floating by, very close to each other, there will not be any interaction. So, I wonder how the simulation outcome would change if you made the predators act more like actual animals who sometimes ignore prey animals and other times seek them out and eat them?

T_Reißig

2026/02/15 22:12:10

You are very right in your ways of thinking through that. I previously looked through the wiki-page my sim is based on and the differential equations are actually based on the assumption that a hunter animal is infinetly hungry. I diverted from that in my scene: If you observe closely you can see that hunters that very recently fed arent interacting with prey animals on collision.

I didn´t include a mechanism that actively navigates hunters towards prey though. On one hand i deemed it too difficult and demanding for my pc to keep the scene running smoothly and on the other hand it probably doesn´t really matter that much.
--> I´d have to balance the hunters following the prey by giving the prey instincts to try to escape. Evolution is so fine-tuned that in the bigger picture it comes down to a game of chance.
--> If you imagine the circles not purely representing an individual hunter but rather their range of perception and a collison as getting within a range at which they can actually percieve prey (f.e. via smell), it is still kind of accurate. If we imagine all hunters to be equally good at hunting it again comes down to a game of chance of who just happens to cross ways with prey and gets to live on and procreate. This chance is mainly determined by number of prey animals (divided by area) as stated in the differential equations.

Last edited at 2026/02/15 22:14:32 by T_Reißig

Xray

2026/02/15 23:46:46

Yes, you made some very good points. I didn't consider the complexity of the programming that would be required to make those circles behave like real animals. It would probably require some modern AI coding which would very likely over-burden many of the devices that most people use to run Algodoo. I enjoy thinking about things like that, not so much as to challenge anyone but rather to spark an interesting discussion such as what you and I are having! That is a great way to learn new things about our amazing world.

T_Reißig

2026/02/16 03:14:03

I very much agree with your last statement.
I happened to play with a scene from another creator recently, where predatory "Cells" actually proactively followed their prey. The creators solutions was via a code written into lasers attached to the hunter. It looked surprisingly realistic, but would probably be next to impossible to incorporate into my scene where a large number of hunters spawns and dies rapidly.
If you want to look it up it was probably called something like "cell petri-dish"

Last edited at 2026/02/16 03:22:10 by T_Reißig