2,571 research outputs found
Stigmergy in Web 2.0: a model for site dynamics
Building Web 2.0 sites does not necessarily ensure the success of the site. We aim to better understand what improves the success of a site by drawing insight from biologically inspired design patterns. Web 2.0 sites provide a mechanism for human interaction enabling powerful intercommunication between massive volumes of users. Early Web 2.0 site providers that were previously dominant are being succeeded by newer sites providing innovative social interaction mechanisms. Understanding what site traits contribute to this success drives research into Web sites mechanics using models to describe the associated social networking behaviour. Some of these models attempt to show how the volume of users provides a self-organising and self-contextualisation of content. One model describing coordinated environments is called stigmergy, a term originally describing coordinated insect behavior. This paper explores how exploiting stigmergy can provide a valuable mechanism for identifying and analysing online user behavior specifically when considering that user freedom of choice is restricted by the provided web site functionality. This will aid our building better collaborative Web sites improving the collaborative processes
An adaptive stigmergy-based system for evaluating technological indicator dynamics in the context of smart specialization
Regional innovation is more and more considered an important enabler of
welfare. It is no coincidence that the European Commission has started looking
at regional peculiarities and dynamics, in order to focus Research and
Innovation Strategies for Smart Specialization towards effective investment
policies. In this context, this work aims to support policy makers in the
analysis of innovation-relevant trends. We exploit a European database of the
regional patent application to determine the dynamics of a set of technological
innovation indicators. For this purpose, we design and develop a software
system for assessing unfolding trends in such indicators. In contrast with
conventional knowledge-based design, our approach is biologically-inspired and
based on self-organization of information. This means that a functional
structure, called track, appears and stays spontaneous at runtime when local
dynamism in data occurs. A further prototyping of tracks allows a better
distinction of the critical phenomena during unfolding events, with a better
assessment of the progressing levels. The proposed mechanism works if
structural parameters are correctly tuned for the given historical context.
Determining such correct parameters is not a simple task since different
indicators may have different dynamics. For this purpose, we adopt an
adaptation mechanism based on differential evolution. The study includes the
problem statement and its characterization in the literature, as well as the
proposed solving approach, experimental setting and results.Comment: mail: [email protected]
Tracking Information Flow through the Environment: Simple Cases of Stigmerg
Recent work in sensor evolution aims at studying the perception-action loop in a formalized information-theoretic manner. By treating sensors as extracting information and actuators as having the capability to "imprint" information on the environment we can view agents as creating, maintaining and making use of various information flows. In our paper we study the perception-action loop of agents using Shannon information flows. We use information theory to track and reveal the important relationships between agents and their environment. For example, we provide an information-theoretic characterization of stigmergy and evolve finite-state automata as agent controllers to engage in stigmergic communication. Our analysis of the evolved automata and the information flow provides insight into how evolution organizes sensoric information acquisition, implicit internal and external memory, processing and action selection
Stigmergy-based modeling to discover urban activity patterns from positioning data
Positioning data offer a remarkable source of information to analyze crowds
urban dynamics. However, discovering urban activity patterns from the emergent
behavior of crowds involves complex system modeling. An alternative approach is
to adopt computational techniques belonging to the emergent paradigm, which
enables self-organization of data and allows adaptive analysis. Specifically,
our approach is based on stigmergy. By using stigmergy each sample position is
associated with a digital pheromone deposit, which progressively evaporates and
aggregates with other deposits according to their spatiotemporal proximity.
Based on this principle, we exploit positioning data to identify high density
areas (hotspots) and characterize their activity over time. This
characterization allows the comparison of dynamics occurring in different days,
providing a similarity measure exploitable by clustering techniques. Thus, we
cluster days according to their activity behavior, discovering unexpected urban
activity patterns. As a case study, we analyze taxi traces in New York City
during 2015
A stigmergy-based analysis of city hotspots to discover trends and anomalies in urban transportation usage
A key aspect of a sustainable urban transportation system is the
effectiveness of transportation policies. To be effective, a policy has to
consider a broad range of elements, such as pollution emission, traffic flow,
and human mobility. Due to the complexity and variability of these elements in
the urban area, to produce effective policies remains a very challenging task.
With the introduction of the smart city paradigm, a widely available amount of
data can be generated in the urban spaces. Such data can be a fundamental
source of knowledge to improve policies because they can reflect the
sustainability issues underlying the city. In this context, we propose an
approach to exploit urban positioning data based on stigmergy, a bio-inspired
mechanism providing scalar and temporal aggregation of samples. By employing
stigmergy, samples in proximity with each other are aggregated into a
functional structure called trail. The trail summarizes relevant dynamics in
data and allows matching them, providing a measure of their similarity.
Moreover, this mechanism can be specialized to unfold specific dynamics.
Specifically, we identify high-density urban areas (i.e hotspots), analyze
their activity over time, and unfold anomalies. Moreover, by matching activity
patterns, a continuous measure of the dissimilarity with respect to the typical
activity pattern is provided. This measure can be used by policy makers to
evaluate the effect of policies and change them dynamically. As a case study,
we analyze taxi trip data gathered in Manhattan from 2013 to 2015.Comment: Preprin
Stigmergic epistemology, stigmergic cognition
To know is to cognize, to cognize is to be a culturally bounded, rationality-bounded and environmentally located agent. Knowledge and cognition are thus dual aspects of human sociality. If social epistemology has the formation, acquisition, mediation, transmission and dissemination of knowledge in complex communities of knowers as its subject matter, then its third party character is essentially stigmergic. In its most generic formulation, stigmergy is the phenomenon of indirect communication mediated by modifications of the environment. Extending this notion one might conceive of social stigmergy as the extra-cranial analog of an artificial neural network providing epistemic structure. This paper recommends a stigmergic framework for social epistemology to account for the supposed tension between individual action, wants and beliefs and the social corpora. We also propose that the so-called "extended mind" thesis offers the requisite stigmergic cognitive analog to stigmergic knowledge. Stigmergy as a theory of interaction within complex systems theory is illustrated through an example that runs on a particle swarm optimization algorithm
Why is Open Access Development so Successful? Stigmergic organization and the economics of information
The explosive development of "free" or "open source" information goods
contravenes the conventional wisdom that markets and commercial organizations
are necessary to efficiently supply products. This paper proposes a theoretical
explanation for this phenomenon, using concepts from economics and theories of
self-organization. Once available on the Internet, information is intrinsically
not a scarce good, as it can be replicated virtually without cost. Moreover,
freely distributing information is profitable to its creator, since it improves
the quality of the information, and enhances the creator's reputation. This
provides a sufficient incentive for people to contribute to open access
projects. Unlike traditional organizations, open access communities are open,
distributed and self-organizing. Coordination is achieved through stigmergy:
listings of "work-in-progress" direct potential contributors to the tasks where
their contribution is most likely to be fruitful. This obviates the need both
for centralized planning and for the "invisible hand" of the market
Stigmergic epistemology, stigmergic cognition
To know is to cognize, to cognize is to be a culturally bounded, rationality-bounded and environmentally located agent. Knowledge and cognition are thus dual aspects of human sociality. If social epistemology has the formation, acquisition, mediation, transmission and dissemination of knowledge in complex communities of knowers as its subject matter, then its third party character is essentially stigmergic. In its most generic formulation, stigmergy is the phenomenon of indirect communication mediated by modifications of the environment. Extending this notion one might conceive of social stigmergy as the extra-cranial analog of an artificial neural network providing epistemic structure. This paper recommends a stigmergic framework for social epistemology to account for the supposed tension between individual action, wants and beliefs and the social corpora. We also propose that the so-called ‘‘extended mind’’ thesis offers the requisite stigmergic cognitive analog to stigmergic knowledge. Stigmergy as a theory of interaction within complex systems theory is illustrated through an example that runs on a particle swarm optimization algorithm.Social epistemology; Extended mind; Social cognition; Particle swarm optimization
Stigmergic hyperlink's contributes to web search
Stigmergic hyperlinks are hyperlinks with a "heart beat": if used they stay healthy and online; if
neglected, they fade, eventually getting replaced. Their life attribute is a relative usage measure that
regular hyperlinks do not provide, hence PageRank-like measures have historically been well
informed about the structure of webs of documents, but unaware of what users effectively do with
the links.
This paper elaborates on how to input the users’ perspective into Google’s original, structure centric,
PageRank metric. The discussion then bridges to the Deep Web, some search challenges, and how
stigmergic hyperlinks could help decentralize the search experience, facilitating user generated
search solutions and supporting new related business models.info:eu-repo/semantics/publishedVersio
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