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Thanks to this article in the Discover Magazine I found this small video on Slatev.com where the basics of pheromone recruitment in ants are explained and where their potential applications in car traffic management are introduced.

As indicated in their name, leaf-cutter ants cut tree leaves and bring the pieces to their nest where they are used as substrate to grow mushrooms. Usually, when the path toward the nest is clean, these pieces of leaf are large. But when the path is obstructed by twigs for instance under which ants have to pass, are they still able to supply their nest with a sufficient amount of leaves? This question was investigated by Audrey Dussutour and her collaborators in a recent article published in Animal Cognition. Hereafter is the abstract of this article that summaries their results better than I could do.

“In this paper we investigate the flexibility of foraging behavior in the leaf-cutting ant Atta colombica, both at the individual and collective levels, following a change in the physical properties of their environment. We studied in laboratory conditions the changes occurring in foraging behavior when a height constraint was placed 1 cm above part of the trail linking the nest to the foraging area. We found that the size and shape of the fragments of foraging material brought back to the nest were significantly modified when the constraint was placed on the trail: independent of their size, forager ants cut smaller and rounder fragments in the presence of a height constraint than in its absence. This size adjustment does not require any direct sensory feedback because it occurred when the ants cut fragments in the foraging area; no further cutting was done when they encountered the constraint. This points to the existence of a template that ants store and use as a reference to adjust their reach while cutting. Remarkably, despite the decrease in the foraging material brought to the nest per capita the colony was still able to improve its foraging performance by doubling the number of transporters. This study illustrates the flexibility of foraging behavior exhibited by an ant colony. It provides a rare example of insects finding an intelligent solution to a problem occurring in a foraging context, at both the individual and collective levels.”

And to illustrate these findings, hereafter is a short video that was published by the New Scientist:

Du 19 au 24 octobre prochain, le Centre de Recherches sur la Cognition Animale (CNRS-URM 5169) et l’Institut de Mathématiques de Toulouse (CNRS-UMR 5219) de l’Université Paul Sabatier à Toulouse organisent la première "Ecole d’Automne interdisciplinaire de Biologie Systémique". Pour cette première édition, le thème abordé sera l’analyse et la modélisation des déplacements individuels et collectifs dans les systèmes biologiques.

Cette école est organisée avec le soutien du CNRS et de l’ANR et s’adresse principalement à des étudiants doctorants et des chercheurs appartenant à différentes disciplines scientifiques (éthologie, écologie, physique et mathématiques appliquées).

Cette école interdisciplinaire se donne comme objectif de fournir une présentation assez large des outils d’acquisition, de traitement statistique et de modélisation du déplacement d’organismes biologiques à différents niveaux d’organisation.

Cette école comprendra :

1. Des introductions générales aux outils d’acquisition et d’analyse des trajectoires,
2. Des cours d’introduction à l’analyse et à la modélisation des interactions entre organismes,
3. Des cours portant sur les modèles physiques et macroscopiques des déplacements collectifs,
4. Des ateliers portant sur l’analyse statistique de trajectoires et la simulation numérique de déplacements
5. Des conférences et tables rondes animées par des biologistes et physiciens autour de l’objet "déplacement".

 Pour plus de renseignements, vous pouvez consulter le site de l’école : http://cognition.ups-tlse.fr/biosys08/.

The IEEE Swarm Intelligence Symposium 2008 will held this year in Saint Louis (Missouri, USA) from September 21 to 23. The call for paper has been recently published and can be downloaded here. They invite authors to submit original and unpublished work related to swarm intelligence, including research, theory, development, and applications. Areas of focus include particle swarm optimization, ant colony swarms, cultural algorithms, foraging techniques, and other swarm-related topics.

Authors are invited to submit their original and unpublished work in the areas including, but not limited to, the following:

1. Modeling and analysis of particle swarm optimization, Ant colony optimization, culture algorithm, foraging algorithm.

2. Optimization techniques in dynamic, multi-objective, constrained environment. Modeling and analysis of biological collective systems such as social insects colonies, school and flocking vertebrates.

3. Distributed computing, machine learning, data mining, data clustering, graph partitioning, and decision making based on swarm intelligence principles.

4. Theory and applications of swarm intelligence principles to real world problems including control systems, evolvable hardware, power system, sensor networks, bioinformatics, business and finance, supply-chain management, planning and operations in industrial systems, transportation systems, and others areas.

Important dates and dead-lines are:

• Tutorial/Special Session Proposals: April 15, 2008.
• Paper Submission: May 15, 2008.
• Notification: June 15, 2008.
• Camera-Ready: July 15, 2008.
• Conference: September 21-23, 2008.

 

Du 14 au 17 avril prochain auront lieu à Toulouse les 4èmes rencontres "Ecologie et Comportement". Ces rencontres organisée par et pour les doctorants et post-doctorants entrent dans le cadre général de l’écologie comportementale, discipline au carrefour de l’étude du comportement animal (l’éthologie), de l’écologie et de la biologie évolutive. Le colloque sera accueilli à Toulouse, par l’Ecole Nationale de Formation Agronomique (ENFA).  Ces rencontres seront entièrement anglophones. L’assistance aux présentations est gratuite. Toutes les informations concernant cet événement sont disponibles à cette adresse : http://www.uappu.org/serl/pmwiki.php.

From April 14th to 17th 2008 the fourth «Meeting in Ecology and Behaviour» will be held in Toulouse. The meeting is entirely organized by PhD and post-doc students and is dedicated to the wide field of Behavioural Ecology: a discipline at the intersection between Animal Behaviour, Ecology, and Evolution. The meeting will be held at the "Ecole Nationale de Formation Agronomique" (ENFA). All the talks will be held in English. Attendance to all talks is free of charge. More information are available at the following address: http://www.uappu.org/serl/pmwiki.php.

###

Deux soirées, ouvertes au public, seront consacrées à une conférence plénière et à la projection d’un documentaire, toutes deux suivies d’un débat. / A plenary talk and a documentary projection followed by a debate will be opened to the public.

Pierre-Henri Gouyon, Professeur au Muséum d’Histoire Naturelle de Paris / Professor at the National Museum of Natural History
Titre de la conférence / Title of the conference: Génétique et évolution : recherche et société / Genetics and evolution: research and society.
Lundi 14 avril à 20h30 / Monday 14th April at 8.30 pm
Lieu : amphithéâtre du Muséum d’Histoire Naturelle de Toulouse / Location: lecture hall of the Toulouse’s Museum of Natural History

Jérôme Orivel et Raphaël Jeanson, chercheurs au CNRS / researchers at the CNRS
Titre du documentaire : "L’organisation secrète des fourmis", suivi d’un débat. / Title of the documentary: "Ants - Nature’s secret power", followed by a debate.
Mardi 15 avril à 21h00 / Tuesday 15th April at 9 pm
Lieu : amphithéâtre 30 sur le campus de l’ Ecole Nationale de Formation Agronomique (ENFA). / Location: lecture hall 30 at the "Ecole Nationale de Formation Agronomique" (ENFA)

Alex Wild is among the most talented insect photographers that can be found by browsing the web. His two web galleries (myrmecos.net and alexanderwild.com) display some of the most beautiful photographs of ants I ever seen (as the one above which is the banner of his blog). He recently published on his blog (the Myrmecos Blog) some good tips and tricks for keeping ants quiet as they are photographed. Always useful when trying to take pictures of these tiny and speedy insects. He also put on his blog some other helpful photo technique articles.

Scientific American has just published a special edition about robotics. It gathers many interesting articles about most of the current hot topics in robotics. Among them is a new version of "Swarm Smarts", an article written by Eric Bonabeau and Guy Theraulaz in 2000 for the same journal, where the approach of swarm intelligence is well summarized. And if you are careful, you should find some pictures about my work with robots Alice.

I recently read the following post by Zyxo on Mixotricha blog about complexity which illustrates one fundamental flaw in many studies of swarm intelligence: the assumption that the subunits in a swarm-intelligent system are necessarily dumb.

"Interesting post from Ryan Hollingsworth as guest blogger for LeRon Shults about swarm intelligence. At the end he poses the above question : can people develop a swarm intelligence ? My answer is simple : NO ! In nature you have species who developed almost no intelligence whatsoever, like plants, amoebae, worms, muscles etc. Other species developed a swarm intelligence, like ants, bees and termites. And at last there are a whole lot of species with a non-neglectable intelligence like all mammals of which we think of ourselves as being the summit. In order for humans to develop a swarm intelligence we should first lose our personal intelligence ! Remember, as I said in a previous post a swarm intelligence is far more intelligent than its constituents ! So, even if we developed a “human swarm intelligence” we would be too stupid to understand it, probably we would’t even notice it. Hence: who says it is’nt already there ?"

A swarm intelligent systems is a system composed of numerous units that collectively solved a problem without supervision. Such a system mainly use self-organization mechanisms to solve problems, that is it triggers the emergence of a functional collective behaviour from a balance between positive and negative feedbacks supported by the repeated direct or indirect interactions between the components of the system.

Such functional and unsupervised collective behaviours are widespread in a large number of gregarious species (if not all), including bacteriae, insects, fish, birds, mammals and even human beings. I recently wrote a post "Swarm intelligence at digg.com" about an example of swarm intelligence in human beings: the selection of interesting news on digg.com. A "human swarm intelligence" therefore exists.

The question is now: why human beings, self-proclaimed most intelligent species on Earth, use self-organization and unsupervised problem solving? To answer this question I will steal some arguments to the following article by Thomas Seeley: When Is Self-Organization Used in Biological Systems?, Biological Bulletin, 2002, 202, 314-318.

Collectively solving a problem with a supervised approach requires that one agent is able to acquire all the relevant information, to compute a solution to the problem and to communicate orders to the other agents. If either the acquisition or the treatment or the emission of the information or any combination of these three delayed the execution of the solution beyond a reasonable time, the supervision can not be efficient to solve the problem.

The ratio between the information load and the speed of information processing is therefore critical in collective problem solving. And even human beings have limits to their cognitive abilities: we can not acquire, treat and send more than a certain amount of data in a given period of time. As Thomas Seeley said, the agents "might possess cognitive abilities that are high in an absolute sense, but low relative to what is needed to effectively supervise a large system". When these limits are oversteped, individuals’ decisions rely only on a partial information and in such a case self-organization is often more adapted than supervision. It is therefore not necessary that we lost our personal intelligence to develop a swarm intelligence.

At last, our implication in a self-organized system does not restrict our understanding of this system. For instance, it is quite easy to understand why and how news are selected at digg.com. But it is surely difficult to achieve the same result with a system fully supervised by only one person because the amount of daily information to explore is incredibly large. Here is probably the main difference between social insects and us: we are able to understand and even to invent an unsupervised system to which we participate.

I recently read a paper by Fang Wu and Bernardo Huberman called "Novelty and collective attention". This paper speak about how attention to novel items propagates and eventually fades among large populations. In particular, they analyzed the dynamics of collective attention among 1 million users of the interactive website digg.com. This website allows its users to submit news stories they find while they browse the internet. Each new submission can be read by other members. If they find it interesting, they can add a digg point to it. The number of digg a submission received is displayed next to each story’s headline and indicates how many users where interested in this news. Moreover, The more digg a news received in a given period of time, the more visible to the audience of the website it becomes and the more likely it receives additionnal digg. Most popular news eventually reach the digg.com frontpage. We have here a positive feedback that tends to highlight the news that are interesting for most of the website users.

Wu and Huberman proposed that this positive feedback is counterbalanced by a negative one driven by the decay in novelty of the news: the older a news, the less it interests people and the less potentially interested people remain uninformed. After a certain time, the news receives less and less digg and gets replaced by newer stories.

The paper of Wu and Huberman particularly interested me because of the striking similarities ants foraging behaviour. Ants communicate with each other through the use of pheromones. These pheromones are chemical substances that attract other ants. For instance, once an ant has found a food source, she quickly comes back to the nest and lays down a pheromone trail. This trail will then guide other workers from the nest toward the food source. When the recruited ants come back to the nest, they lay down their own pheromone on the trail and reinforce the pathway. The trail formation therefore results from a positive feedback: the more ants use a trail, the more attractive the trail becomes.

Interestingly when several food sources are available, workers modulate their trail-laying intensity as a function of the quality of the food source. Workers therefore preferentially select and reinforce rich food sources while pheromone evaporation little by little wipe out the paths towards poor ones. This competition between rich and poor sources eventually directs the colony activity on the most profitable option. If the selected food source run out, ants stops laying pheromone and eventually the trail vanishes allowing the exploitation of other food sources.

In these two ewamples, a transfer of information occurs thanks to stigmergic (or indirect) interactions. An individual having an information releases in the environment a suitable signal that can be used by another individual at a later time. This signal is a pheromone deposit in ants and a digg point in humans. Then a reinforcing mechanism enhances the constrast between different information and put forward the one that presents an interest for most of (if not all) the individuals. The transitional nature of the signal substrate (chemicals in ants, attention in human beings) allows the collective system to retain this information for a certain period of time and then to drop it once it becomes not profitable/interesting anymore.

For more information:

1. Novelty and collective attention. Fang Wu and Bernardo Huberman. Proceedings of the National Academy of Sciences, 2007, p. 0704916104.
2. The biological principles of swarm intelligence. Simon Garnier, Jacques Gautrais and Guy Theraulaz. Swarm Intelligence, 2007, vol. 1, pp. 3-31.
3. Bernardo Huberman conference at ECCS.
4. Guy Theraulaz conference at ECCS.

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