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Among all the insects who can live no more than several months, ants on the other hand can live up to 30 years !!

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The ant is one of the world’s strongest creatures compared to its size.

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The ant is one of the world’s strongest creatures compared to its size.

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A single ant can carry 50 times its own bodyweight !!

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Ants can be found on every continent except Antarctica and Arctic

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Ants can be found on every continent except Antarctica and Arctic

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Ironically, when you consider the name

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www.natgeokids.com

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Sometimes ant colonies will combine forces and work together.

These super colonies are connected through trails that link the nests together

Argentine and red fire ants are known to create super colonies.

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Ants are social insects, which mean they live in groups. When you see one or two ants walking in your house, they often belong to a colony. Ants live in colonies that are made of different castes.

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Ants don’t have lungs for breathing air; they have tiny holes on their body to absorb the oxygen from the air.

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Ants use their powerful mandibles to grasp and carry, as well as for cutting and biting.

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When ants find food they emit pheromones that provide scent trails so their nest mates can find the food.

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Coding Adventure: Ant and Slime Simulations

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9:13 : Unleashing the ants.

Sebastian Lague is one of my favourite youtubers. He uses some fascinating visualisation techniques to illustrate complexe topics.

He simulates in this video the Well known ants colony algorithm in computer science!

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Coding Adventure: Ant and Slime Simulations

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The ant colony algorithm is an algorithm for finding optimal paths that is based on the behavior of ants searching for food.

At first, the ants wander randomly. When an ant finds a source of food, it walks back to the colony leaving "markers" (pheromones) that show the path has food. When other ants come across the markers, they are likely to follow the path with a certain probability. If they do, they then populate the path with their own markers as they bring the food back. As more ants find the path, it gets stronger until there are a couple of streams of ants traveling to various food sources near the colony.

Because the ants drop pheromones every time they bring food, shorter paths are more likely to be stronger, hence optimizing the "solution." In the meantime, some ants are still randomly scouting for closer food sources.

Once the food source is depleted, the route is no longer populated with pheromones and slowly decays.

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My motivation/inspiration for the subject?

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My motivation/inspiration for the subject?

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I first was introduced to this topic by the Sebastian Lague video back in high school. From that time I was following his wonderful science journey.

The way ants are behaving, adapting and using the most of their available ressources to accomplish their missions inside the colony is fascinating considering the fact that animal intelligence is not that valued.

Their wy of optimising the food paths is used in huge industrial algorithmic solvers to maximise profits and gains.

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The impact of nature and organic organisms on the advancements of science and technologies is considerable.

Thus curiosity, observation and inspecting different aspects of nature should be the main skills of a scientist and a truth seeker.

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Main information sources:

1. NatGeoKids :Fun facts

2. Youtube: Sebastian Lague

3. Harbard Forest article

4. Math world wolfram

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How was your work organized? How did it evolve over time?

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How was your work organized? How did it evolve over time?

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I chose another topic before (computational life), the roadmaps was unclear and vast. After that I pivoted to ants simulation.

This topic is well integrated with the course and has a lots of interesting data.

I first gathered some basic information from different websites.

Than I filtered the some clear and easy to digest information.

Some medias were also helpful for illustration.