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why an element occurred in a system). Rather – once
it is there – how it develops, interacts with other enti-
ties, changes and influences more complex structures.
From this perspective, the frequency-based approach
seems to provide an explanation of the evolutionary
processes occurring in any system. It opens a new
perspective of looking at the problem of evolution in
“natural” system and link the findings to digital envi-
ronments. From the linguistic point of view, there is
still a lot of research to be done. The role of frequency
has been analysed in a variety of languages. However,
an intricate question “is this frequency-based hypoth-
esis true for every language?” still remains unan-
swered. Furthermore, the aspect of network topolo-
gies needs further investigations. The role of fre-
quency in different types of networks would provide
more general picture of the evolutionary processes.
The understanding of underlying laws and forces
of language evolution helps with creating systems
that are both adaptable to user needs and are self-
organised. As Grudin and Norman (Grudin and Nor-
man, 1991) pointed out:
the analyses of natural languages and design
of interactive computer systems reveal many
of the same pressures. In both communication
media, these pressures lead to innovations in
the structure of the medium, inconsistencies,
and a continual tension between expressive-
ness, ease of use, ease of understanding, and
ease of learning.
These pressures seem to be the power and efficiency
underlain by the mechanism of frequency. Therefore,
consideration of this aspect needs to be taken into
account during the design and development of a dy-
namic system (knowledge systems, networks, and in-
terfaces), in general, and specific algorithms that build
up such a system, in particular.
ACKNOWLEDGEMENTS
This research is conducted as part of the task
“Evolutionary Framework for Language” within the
interdisciplinary project (Network of Excellence)
Open Philosophies for Associative Autopoietic Dig-
ital Ecosystems (OPAALS) (http://www.opaals.org).
REFERENCES
Barab
´
asi, A., Dezso, Z., Ravasz, E., Yook, S., and Oltvai,
Z. (2003). Scale-free and hierarchical structures in
complex networks. AIP Conference Proceedings, 661.
Briscoe, G. and Wilde, P. D. (2006). Digital ecosystems:
Evolving service-oriented architectures. In Confer-
ence on Bio Inspired Models of Network, Information
and Computing Systems. IEEE Press.
Cancho, F. I. R., Riordan, O., and Bollob
´
as, B. (2005). The
consequences of zipf’s law for syntax and symbolic
reference. In Proceedings of the Royal Society, pages
561–565.
Cancho, F. I. R. and Sol
´
e, R. V. (2001). The small
world of human language. Proceedings of The Royal
Society of London. Series B, Biological Sciences,
268(1482):2261–2265.
Dini, P., Rathbone, N., Vidal, M., Hernandez, P., Ferronato,
P., Briscoe, G., and Hendryx, S. (2005). The digital
ecosystems research vision: 2010 and beyond.
Ferreira, A. A. A., Corso, G., Piuvezam, G., and Alves, M.
S. C. F. (2006). A scale-free network of evoked words.
Brazilian Journal of Physics, 36(3):755–758.
Grudin, J. and Norman, D. (1991). Language evolution and
human-computer interaction. In Proceedings of the
13th Annual Conference of the Cognitive Science So-
ciety, pages 611–616.
Haspelmath, M. (2008a). Creating economical morphosyn-
tactic patterns in language change. In Good, J., editor,
Language Universals and Language Change, pages
185–214. Oxford University Press, Oxford.
Haspelmath, M. (2008b). Frequency vs. iconicity in ex-
plaining grammatical asymmetries. Cognitive Lin-
guistics, 19(1):1–33.
Huang, C.-Y., Sun, C.-T., and Lin, H.-C. (2005). Influence
of local information on social simulations in small-
world network models. Journal of Artificial Societies
and Social Simulation, 8(4):8.
Liu, H. and Hu, F. (2008). What role does syntax play in a
language network? Europhysics Letters, 83.
Liu, J., Wang, J., and Wang, C. (2008). Research on text
network representation. In IEEE International Con-
ference on Networking, Sensing and Control, ICNSC
2008, pages 1217–1221.
Motter, A. E., de Moura, A. P. S., Lai, Y.-C., and Dasgupta,
P. (2002). Topology of the conceptual network of lan-
guage. Physical Review E, 65(6).
Oller, D. (2004). Underpinnings for a Theory of Commu-
nicative Evolution, pages 49–65. MIT Press, Cam-
bridge.
Sole, R. V., Corominas, B., Valverde, S., and Steels, L.
(2005). Language networks: their structure, function
and evolution. Trends in Cognitive Sciences.
Steels, L. (2004). Social and Cultural Learning in the Evo-
lution of Human Communication, pages 69–90. MIT
Press, Cambridge.
Tullo, C. and Hurford, J. (2003). Modelling zipfian distri-
butions in language. In Kirby, S., editor, Proceedings
of Language Evolution and Computation Workshop,
pages 62–75, Vienna.
Worden, R. (1995). A speed limit for evolution. Journal of
Theoretical Biology, 176:137–152.
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