C++ Ants Simulation 5, Ants Fight 

1000 + 1000 + 1000 + 1000 = 4000

it says its not good

The release is fullscreen but seemingly only 1080p, which messes with my desktop since I have a 1440p monitor. Is it possible to have it run in a window, or switch to the native resolution? I'd rather not mess with the source code myself, as I've had little luck compiling C-related code for whatever reason.

@@shuriken188 I've just updated the release link to add a conf file alongside the executable with configurable window size and mode

@@PezzzasWork Awesome

And sometimes they either start to fight, or start to form 'supercolonies', which are colonies with multiple queens.

YES

@@Zedryx69 in nature, this behavior is dependent on species. Most ants fight with child colonize, some ants form global colonize who rage war over several continents.

Aother small possible addition: Corpses become food.

@@Zedryx69 Then you have team competitions not just FFAs

Hope you will like it :)

You're not the only one

Same

amen

Same

hehe "evolve"

me too hahah

Yeah, from what i saw, there are a few factors in play, they are: 1. How close are the nearest resource points? 2. How many are there? 3. Are there any bordering colonies? 4. Do they have access to more resource points than you do? 5. Are you close to the middle / have a clear path? There are probably more, but in my opinion these are quite important, if not the most important.

@@MostScaryCat Yea, I noticed that proximity to more resources than the closest colony is a very strong advantage. Didn't think about the clear path but looking again it does make a significant difference.

@@MostScaryCat I found that those who branched out and discovered new resource piles earlier tended to win, especially those that established strong connection lines by the time fighting begins

That's a good idea

@@mementomori7160 hmmm

some types of ants have nurses too (but I don't know how that could be added)

There is just workers and soldiers, it’s just that in this simulation ants are able to follow a path but have different genes compared to everyone else, making them take unique paths that happen to make some ants go off-course and end up finding other resources or areas.

@@CosmicCrimson your right however some species have specific worker ants (for example nurses and explorers) so even if there are only worker and soldier ants there can still be other types of worker ants

With the main question being 'How can I influence this to get the victory?'.

​@@Bloodlyshiva A while back, I wrote something similar to this to run on the GPU, the best ways of implementing player control would be. 1. Instruction pheromone - allow the player to paint pheremone directly - allowing them to "soft direct" ants at will (to attack other colonies, get a certain resource etc) 2. Population control, allow the user to dynamically set ant production rates for new nests vs worker ants - kinda boom vs rush style 3. Tech trees, allow you to improve speed, attack strength, or other stats which costs foods that the ants collect

Lord of the ants it's basically just lord of the Rings but with ants

just play starcraft and choose zerg

Thank you for this remark!

@@PezzzasWork I'm glad to be of assistance! Keep up the amazing work!

Since the project is open source, I guess someone can port it to android.

theres a game like it lol, but you can play it yourself and control things. mobile and online game

@@miniiogaming6954 Name please

@@miniiogaming6954 name please

@@moments4258 the only game I can think of is "Pocket Ants". Played it for a while, quite fun. You actually play as an "ant commander", so it's quite different from this but quite the same I guess

Dead ants to be used as food?

so kinda like people in a way?

@@vaibhavbv3409 I'm not an ant expert but i don't think ants eat dead ants

@@alansus586 they eat dead ant, but not the same colony one

Ant understand how to produce food for them

C++ ants create create C++ humans simulation

Ants do photosynthesis

hopefully next episode

soon, the workers will have pickaxes and the soldiers will have worker machine guns.

@@MostScaryCat and also soon the spies are going ninja stars and ranged soldiers are going to have shields

Ant ideologies

@@Nugcon Fasticm can be one where they are fast

Very true through the entire video I saw two main deciders for who wins and that is isolation & least distance to the most amount of food(usually this would be the mid). Although on the fourth blue won because it was able to take hold of some uncontested piles of food by taking out red and it had a pretty short path to the mid.

You mean thanks for "wathing" :D

Yes please! I am hoping different stats will be better at different maps

I would agree. The sooner an ant can bring its food back the sooner it can go to collect more. Having closer food means more throughput, which means faster population growth, which translates to more efficient food gathering from farther food sources. A closer starting food source snowballs quite quickly. I wonder how the ants would do with chokepoints, infinite food sources, and imbalanced maps. For instance, could a colony with only a single infinite food source outlast a colony with many finite food sources if there's a choke point to defend?

@@Zebo12345678 That's pretty interesting. I think it would also be interesting to see the simulation run against those scenarios, but also the 'latent space' between them. So if there is a 1v1 map with a central food source, and I wonder what happens if one nest was further away or if there was an obstacle in the way or if the food had different shapes and cavities... Those scenarios may be interesting but if we call the map a picture and take a geometric 'morph' between the map of the base scenario and a modified scenario and we simulate on each of the maps generated by each step in the morph, that could also yield interesting results. Perhaps to watch something like that (in a timely manner) the videos would need to be layered over each other with each iteration using a slight brightness or hue shift or something. I just think it would be cool to have an idea of why a scenario plays out a certain way and watch to see if it's possible to determine, as a scenario changes little by little and morphs into the alternate scenario, when a result should change and why. Like, if there is a 1v1 open map except for a wall with a tiny gap between competing nests, and one nest has a nearby food source and the other a more distant food source, then if the gap is small enough, it could be difficult to press the advantage of faster growth. Seeing what happens as the gap opens wider each iteration until the advantage could be pressed and trying to predict when such a thing could happen, would be interesting.

@@solerante That's a great idea too. These simulations are kind of addictive, huh?

It's open source, you can check the description for a link

I've just started learning Bevy and had the same thought. Did you end up getting anywhere with this?