Cemetery Emergence

This simulation shows how a unique cemetary can emerge in a ant colony without any communication between ants nor a global intelligence controlling all ants.

Each ant act independantly, if it finds a dead ant close to the anthill it put it away at a safe sanitary distance and create a new cemetary. If it finds a bigger cemetary it will consider it the new one and start to move the previous one in this one.

We can see in this video that after some time a unique cemetary emmerges at a safe distance from the anthill.

Go around objects

We have implemented a new feature that let the ants go around object in their way.

If they colide with an object they will go in a go around mode and will choose at random a direction between left and right. This choice is influenced by the pheromones arround. Then they will rotate themself in this direction until they can progress. They keep the same direction as long as the object is at sight to prevent them from always changing direction all the time and follow none in practice.

The going arround object start to look nice but we have performance issues the pheromones that we are trying to solve. When it will be working properly with the pheromones the best side of the object should emmerge from the pheromones left before, since the shortest path should have more pheromones, but for now they just pick a direction at random.

Open source !

Our project goes open source, the svn is now in free checkout under FreeBSD License (which is not currently explicit, but it will be soon).
To get the code, open a terminal and type 'svn checkout http://www.clubnix.fr/svn/aints'. If you are running an alternative OS like Microsoft Windows, then intall some junk shareware/freeware.
Actually you will need the alternative OS to develop on this basis since it is a Visual Studio project... Visual Studio is available for free on MSDNAA for Chalmers students (see this : http://www.chalmers.se/en/sections/education/current_students/it-for-students/software).

First demonstration video

This is a first version of our project . Each ant have a very simple behavior that is the mix between folowing pheromones, folowing a goal, go randomly and come back when they are hungry. And a colony behavior emmerge from this letting them haverest the cloest food points quickly find new food when one is empty.

The yellow circles represents the anthill, the red dots the food points and light orange dots the pheromones that they leave on their way.

The next steps will be to manage the production of ants in the anthill then create competition with other anthills. After that we will differentiate the production of workers and soldiers, and try to make the soldiers production automatically increased in a competitive environment.

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Myrmedrome

We discovered an other project that aims to simulate ants behaviors, which is called Myrmedrome. It is based on some behaviors like pheromones of courses, but also trophalaxis, it differentiates soldiers and workers, and also allows to put insect preys on the map, and to wreck havoc within ants with a finger.
But it is not related to scientific papers like our project will, ours also aims for computer science applications (at least from far away). And in our simulator, ants move freely around the map (and outside), while in Myrmedrome, they follow a tile-based map.
It also appears that the ants in Myrmedrome are not likely to improve path to food by themselves, and will rather follow the first defined path, even not optimal.

So it gives us an aim : to make our project better than this one !

Starting implementation

We started on previous week the implementation of the program, using the XNA framework with C#. It is going pretty well, and we based ourselves on a generic architecture that makes the code easily adaptable, and has proven its efficiency on other projects, so we came pretty quickly to something working.
This means that now that we have the basics working, we will start to do some tests, and implement the more tricky and less known behaviors. Our starting point might be to differentiate soldiers and workers, and implement the behavior of the queen.

Orientation of the project

Ants are widely used in algorithms to resolve complicated problems via many iteration of a simple behavior, there is even a conference held every year an this subject, this year's is the seventh : http://iridia.ulb.ac.be/ants2010/
Based on this, we can hope that the field is pretty much covered by specialists, and there is not so much left for us poor students.
But if we leave algorithms for just a moment and look at real ants, we see that the "ant behavior" used in algorithms is not very close to reality, and the ants are much more interesting than just wandering around and putting some pheromones behind them. So it could be very interesting to try simulating a behavior closer to how real ants act, from the biological and emergence point of view : how single beings without superior authority achieve great things like ants colonies ?
And what if the model that emerges from our work allows some applications in algorithm then ? This totally not impossible, and maybe we won't fall to far away from our first concern : algorithms.

So it seems that we will be working on real ants behavior rather than looking in the well studied field of basic ants algorithms.

for this we will have to read/listen/watch some things about ants. It seems that the book called "The Ants", by Bert Hölldobler and Edward O. Wilson is (was) a reference on this topic in 1990, so it could be interresting to look at it, some parts are available on google books :



and I also found a more recent one, in French, referring to "The Ants" as its inspiration, and willing to gather knowledge about ants adding research issues since 1990. I red the first chapter, which is interesting and with a lot of references :

First try on the project

We did a first try with a flash animation to simulate an ant colony. The anthill is represented by a yellow square, the ants by a black one, the food is red and the obstacles are gray. The ants go randomly at first but they put pheromones on their way, and the other ants will most likely go for a "pheromoned" path. Once a food resource is found, the ant grab one unit of it and bring it back to the anthill following the pheromone path, and making it stronger.
Every time 10 unit of food are gathered a new ant is produced, which will look for more food. In this example two ant colonies are competing with each other, to allow us to compare the choice of different parameters. Here, the top left anthill is using less random parameters, and we can observe that it will generally loose.

We will then upgrade the project by having more ants and get rid of the squares to have a more natural look. Also we may try to use a genetic algorithm to find the parameters that lead to the most efficient and the most realistic behavior.

Presentation of aInts

We created this blog to present the progress of the aInts project. This project, which is part of the artificial intelligence course of Chalmers University, is to develop an ant colony algorithm. One of our inspirations for choosing this subject is the book "Empire of the ants" of the French writer Bernard Werber (more info: see http://www.bernardwerber.com/intro_en.html).

The book is a mix of science fiction, more or less accurate scientific facts and a passionating story. It describes an ant colony organization through a very interesting inside angle and gave us inspiration simulate such behaviors.

The concept of emergence also attracted us, about the magic of having lots of agents with very simple behaviors, and see complex and organized colony behaviors emerge out of it.

We are currently still looking for more information on the subject and thinking on how to narrow the project, but we currently want to focus more on simulation of the colony, having something that look like a real ant colony rather than trying to solve other algorithm problems with it.

The members of the project are:

Myriam Économou

Sonia Kostenko

Éric Hauchecorne

Raphaël Vandon