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EvoSym: (ERA-Net Complexity-Net) Oorsprong en evolutie van biologische symbool systemen. (Emergence and Evolution of Biological Symbol Systems). (FWOAL575)

EvoSym is a collaborative European research project supported under

the Complexity-NET 2009 pilot funding call, Interdisciplinary

Challenges for Complexity Science. Complexity-NET is the European

Network for the Coordination of Complexity Research and Training


The project applies methods and techniques of complexity science to

understand the emergence and evolution of biological "symbol systems"

(also called "biosemiotic systems"), such as genetic coding

(DNA-protein), RNA editing, cell signalling, etc. It also investigates

potential technological applications in distributed agent-based

software and robotics. It aims two anser two key questions:

(1) How do complex representational and communicative coding

systems emerge, self-organise and evolve, from micro to macro levels,

in the natural biosphere? and

(2) How can this biological understanding be applied to the

artificial evolution of complex coding systems in computational and/or

robotic systems?

The project is further structured into three major work packages:

WP1 builds on previous work in modelling prebiotic molecular evolution

in spatially extended individual-based systems. It specifically

considers whether or how "RNA coding" could evolve in such an

environment (Lead partner: Bioinformatics Group, Universiteit


WP2 is a complementary investigation of the origin and evolution of

evolvable coding and translation in purely computational systems -

specifically "coreworlds" (e.g., tierra , nanopond etc.) and

"artificial chemistries", which can model evolving software agents in

networked computer systems (Lead partner: Artificial Life Lab, Rince


WP3 bridges between the other two workpackages, to apply principles of

language evolution in collective robotic systems to the emergence of

complex (i.e., compositional and grammatical) languages in models of

chemical communication among biological cells. (Lead partner:

Artificial Intelligence Laboratory, Vrije Universiteit Brussel.)
Datum:1 jan 2010 →  31 dec 2011
Trefwoorden:Programming, Informatics, Artificial Intelligence, Www
Disciplines:Wiskunde en statistiek