2 Draft Papers: Swarm Search, Self-Regulated Pop. Size and Social Cognitive Maps

[Vitorino RAMOS]

Dear Colleagues:
Two of my recent works can now be found online. hope u could enjoy them.
best regards, vitorino ramos

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Varying the Population Size of Artificial Foraging Swarms on Time Varying 
Landscapes,
final draft submitted to ICCANN -05, International Conf. on Artificial 
Neural Networks,
Springer-Verlag, LNCS series, Warsaw, Poland, Sep. 11-15, 2005.

link: http://alfa.ist.utl.pt/~cvrm/staff/vramos/ref_59.html
PDF direct link: http://alfa.ist.utl.pt/~cvrm/staff/vramos/Vramos-ICANN05.pdf

ABSTRACT: Swarm Intelligence (SI) is the property of a system whereby the 
collective behaviors of (unsophisticated) entities interacting locally with 
their environment cause coherent functional global patterns to emerge. SI 
provides a basis with wich it is possible to explore collective (or 
distributed) problem solving without centralized control or the provision 
of a global model. In this paper we present a Swarm Search Algorithm with 
varying population of agents. The swarm is based on a previous model with 
fixed population which proved its effectiveness on several computation 
problems. We will show that the variation of the population size provides 
the swarm with mechanisms that improves its self-adaptability and causes 
the emergence of a more robust self-organized behavior, resulting in a 
higher efficiency on searching peaks and valleys over dynamic search 
landscapes represented here - for the purpose of different experiments - by 
several three-dimensional mathematical functions that suddenly change over 
time. We will also show that the present swarm, for each function, 
self-adapts towards an optimal population size, thus self-regulating.

KEYWORDS: Swarm Intelligence and Perception, Dynamic Population Sizes, 
Self-Regulation, Social Cognitive Maps, Social Foraging, Self-Organization 
and Evolution, Distributed Search and Optimization.

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Social Cognitive Maps, Swarm Collective 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.

link: http://alfa.ist.utl.pt/~cvrm/staff/vramos/ref_58.html
PDF direct link: http://alfa.ist.utl.pt/~cvrm/staff/vramos/Vramos-BMM.pdf

ABSTRACT: Swarm Intelligence (SI) is the property of a system 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.

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