Evolving AIs - Predator vs Prey, who will win?

I love how the prey can also move backwards at the same speed, meaning they can run away from the predators while staring at them the whole time

As a biologist, I think this simulation could be a useful educational asset for schools! It could be considered as an accurate representation of the Lotka - Volterra model, which presents the changes of prey - predator populations over time.

It was interesting seeing the predator's numbers drop shortly after the prey numbers drop, and seeing them rise when the prey numbers rise. It shows how dependent on prey they were.

Prey's group movements, in the latest stages, are surprisingly similar to those you can see in bird flocks or shoals of fishes

A small modification you can add is making entities use more energy when going especially fast, and practically no energy when moving slowly. This may encourage preds to try searching for prey more than just spinning, and allow prey to dodge more

It's pretty interesting how the prey entities seem to display herd behavior at times. Very nice simulation! Edit: I meant for this to just be a quick comment about what I thought was an interesting pattern emerging in the simulation. I didn't think it would actually get so many likes... I know/knew that prey are not able to see each other, in fact, that's exactly why I thought this was interesting in the first place and many times in nature you can observe what APPEAR to be social behaviors emerging out of asocial processes. Some people seem to think this is an obvious or trivial pattern that is not worth consideration. I wouldn't jump to such a hasty conclusion. Yes, it is true that the herd does not physically stop predators, BUT it does block their line of sight and predators could develop hunting tactics that discourage them from entering the herd (which prey could take advantage of). Over time you may even see societal roles develop in which active individuals circle the outside of the "herd" while avoiding/distracting predators, while sedentary individuals reside within the herd where they thrive (thereby creating these large clusters). I don't know the exact details of the neural network that was implemented here so this is ultimately all just speculation. Perhaps the herds ARE just random areas with higher reproduction rates (although this very fact already suggests an evolutionary advantage to such a structure) but nonetheless I still find this interesting to ponder and analyze. I stand by my original comment that it is an interesting observation and certainly a thought-provoking simulation.

Seriously awesome end screen there, actually did not see that coming, very cool!

Honestly, its so mind-bogglingly interesting that you recreated survival of the fittest in such a simple but thorough demonstration.

Incredible work! Amazing idea & very fun to watch. This "crisis" periods are characteristic of predator-prey models, see e.g. the Lotka–Volterra equations.

This is awesome! Here are some interesting ideas. 1. Add a third entity to simulate foliage. It is static, grows at a steady pace, is eaten/sought out by the prey, and neutral to the predators. This would cause concentrations of areas that the prey will sit similar to feeding grounds/oasis. 2. Set random evolution parameters with speed, energy depletion, digestion, & splitting. With things like capped/floored energy. Quicker or slower speed acceleration. Etc. It'd be interesting to see if low energy, quick accelerator, low cap speed prey outruns a fast energy burning, no capped, floored speed predator. 3. Maturity. Add in a maturity/size variable that dictates speed, energy, etc. Smaller prey gives less energy but is easier to catch, etc.

You should add a grazing effect! Like prey can only regenerate energy and reproduce as they move over the area, but with a lawnmower effect that has to regenerate the resource the prey eat overtime, so the prey can "overgraze" an area in the absence of predators!

I love how by setting such simple rules you could get such a complex result. Evolution AI really is amazing!

its like a second christmas when you upload, love the stuff

Idea: make it, so that each time they split, they randomly change they fov and range of the rays. Those with higher fov and range may for example consume more energy, but they can see so much more. Therefore we would see if finaly evolution decided to go with higher fov and range or lower to consume less energy. Also, cool video. Thanks for likes

So freaking cool! Evolution, prey-predator equilibrium, resource competition. So many things shown in this simulation. Terrific job!

"Hard times create strong men. Strong men create good times. Good times create weak men. And, weak men create hard times."

So interesting! I'd personally love to see two features added: 1. prey grazing. The longer the prey sits in the same spot, eventually that spot has been over-grazed and provides no more energy, so the prey will have to keep migrating around the map for more to eat, while the depleted areas gradually grow back. 2. terrain. Say one corner of the map is "rocky" and movement is halved or quartered, how might predators and prey evolve to be suited for that terrain? Will prey sit up there like mountain goats, while the predators can't get up there to get them before starving? Thanks for making this simulation, and for sharing it with us. I'd love to see more.

It seemed like at some points the predators had "evolved" to leave the herds of prey alive, instead circling around the edges in order to pick off enough to survive, but not kill the food source. More tiers of predator would be interesting, to see if you could create a perpetual cycle of predators that keep each others population down to prevent the extinction events in this video.

This is one of the coolest most entertaining things I have seen in ages! Bravo the concept; and well engaged well produced too. Top class.

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