Re: [Swarm-Modelling] Social Cognitive Maps

[Vitorino RAMOS]

Dear Nelson:

Thanks for your words. You are wrigth. In social bees there are not 
pheromone communication, but still there is Stigmergy. A qualitative kind 
of stigmergy.
Anyway, I could not point any model for that kind of simulation, since 
there are already some differente approaches. For instance, "Marriage in 
Honey-Bees Optimization" Algorithms. Check the work of Hussein A. Abbass:

http://www.cs.adfa.edu.au/~abbass/

Also, last year, on the well famous ANTS conference dedicated each year to 
SWARM INTELLIGENCE, the paper that won the best paper award was based on 
honey-bee behaviour. But unfornately, I had a copy but it's lost. The 
algorithm is named BeeHive:

http://iridia.ulb.ac.be/~ants/ants2004/prize.html

Other works, are very interesting and based on Social Bees Thermoregulation 
abilities.

http://www.comdig.com/send_article.php?id_article=17215

Hope this could help you in someway. Best regards, Vitorino

~ v.ramos [http://alfa.ist.utl.pt/~cvrm/staff/vramos/]




At 10:28 21-02-2005, you wrote:
> Hello Vitorino Ramos,
>
> First I want to congratulate you for your excelent
> work.
>
> I read your paper, that is very interesting.
>
> Can i put you a question?
> - In a bee colony, i think that don't exists
> pheromones, but the knowledge of the environment is
> passed throw some type of movements in the nest to
> indicate to flower fields. What type of model can be
> used to simulate an bee colony?
>
> Best regards,
> Nelson Faria
>
> --- Vitorino RAMOS <address@hidden>
> wrote:
>
> >
> >
> > Social Cognitive Maps, Swarm Perception and
> > Distributed Search on Dynamic
> > Landscapes, CVRM-IST 127E-2005 technical report,
> > final draft submitted to
> > Brains, Minds & Media, Journal of New Media in
> > Neural and Cognitive
> > Science, NRW, Germany, 2005.
> >
> >
> http://alfa.ist.utl.pt/~cvrm/staff/vramos/Vramos-BMM.pdf
> >
> > ABSTRACT: Swarm Intelligence (SI) is the property of
> > a systems whereby the
> > collective behaviors of (unsophisticated) entities
> > interacting locally with
> > their environment cause coherent functional global
> > patterns to emerge. SI
> > provides a basis with which it is possible to
> > explore collective (or
> > distributed) problem solving without centralized
> > control or the provision
> > of a global model. To tackle the formation of a
> > coherent social collective
> > intelligence from individual behaviors, we discuss
> > several concepts related
> > to self-organization, stigmergy and social foraging
> > in animals. Then, in a
> > more abstract level we suggest and stress the role
> > played not only by the
> > environmental media as a driving force for societal
> > learning, as well as by
> > positive and negative feedbacks produced by the many
> > interactions among
> > agents. Finally, presenting a simple model based on
> > the above features, we
> > will address the collective adaptation of a social
> > community to a cultural
> > (environmental, contextual) or media informational
> > dynamical landscape,
> > represented here - for the purpose of different
> > experiments - by several
> > three-dimensional mathematical functions that
> > suddenly change over time.
> > Results indicate that the collective intelligence is
> > able to cope and
> > quickly adapt to unforeseen situations even when
> > over the same cooperative
> > foraging period, the community is requested to deal
> > with two different and
> > contradictory purposes.
> >
> > KEYWORDS: Swarm Intelligence and Perception, Social
> > Cognitive Maps, Social
> > Foraging, Self-Organization, Distributed Search and
> > Optimization.
> >
> > hope u could enjoy it. best, v.
> >
> > ~ v. ramos
> > [http://alfa.ist.utl.pt/~cvrm/staff/vramos/]
> >
> > _______________________________________________
> > Modelling mailing list
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> > http://www.swarm.org/mailman/listinfo/modelling
> >
>
>
>
>
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