Emergence and Evolution of Biological Symbol Systems

Start: 
1 November 2010
End: 
31 October 2012
Funding: 
Complexity-NET

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 Activities.

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?  
  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 Utrecht).
  • 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 Institute.)
  • 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.)
Involved members: 
Research topics: