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Studying complex adaptive systems using molecular classifier systems

Decraene, James and Mitchell, George G. and McMullin, Barry (2007) Studying complex adaptive systems using molecular classifier systems. In: ECCS 2007: European Conference on Complex Systems 2007, 1-5 October 2007 , Dresden, Germany.

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Complex Adaptive Systems (CAS) are dynamical networks of interacting agents occurring in a variety of natural and artificial systems (e.g. cells, societies, stock markets). These complex systems have the ability to adapt, evolve and learn from experience. To study CAS, Holland proposed to employ agent-based systems in which Learning Classifier Systems (LCS) are used to determine the agents behavior and adaptivity. We argue that LCS are limited for the study of CAS: the rule-discovery mechanism is pre-specified and may limit the evolvability of CAS. Secondly, LCS distinguish a demarcation between messages and rules, however operations are reflexive in CAS, e.g. in a cell, an agent (a molecule) may both act as a message (substrate) and as a catalyst (rule). To address these issues, we proposed the Molecular Classifier Systems (MCS.b), a string-based artificial chemistry based on Holland’s Broadcast Language. In the MCS.b, no explicit fitness function is specified, moreover no distinction is made between messages and rules. In the context of the ESIGNET project, we employ the MCS.b to study a subclass of CAS : Cell Signaling Networks (CSNs) which are complex biochemical networks responsible for coordinating cellular activities. As CSNs occur in cells, these networks must replicate themselves prior to cell division. In this poster we present a series of experiments focusing on the self-replication ability of these CAS.

Item Type:Conference or Workshop Item (Poster)
Event Type:Conference
Additional Information:Page 174
Subjects:Computer Science > Artificial intelligence
Computer Science > Algorithms
Engineering > Artificial life
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > Research Institute for Networks and Communications Engineering (RINCE)
Published in:Proceedings of the third European Conference on Complex Systems 2007. .
Official URL:
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:4596
Deposited On:09 Jun 2009 09:29 by James Decraene. Last Modified 09 Jun 2009 09:29

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