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From complex living systems to smarter computers

Date:
March 19, 2013
Source:
Centre for Genomic Regulation
Summary:
Compared to human-made technology, living organisms have an enviable ability to adjust to new situations, make complex decisions, and even to heal themselves when damaged. By contrast, technological systems struggle to cope with the unexpected. An important example of such clever biology is multicellular organization. The millions of cells, which make up an early embryo, can communicate only with their neighbors, and yet they are each capable of making the right decisions so that together they collaborate to build organs and whole bodies. Understanding how they achieve this will not only benefit biomedical research, but could also help us to build more intelligent technology.
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The European collaborative research Project "SWAM-ORGAN" tries to understand complex living systems such as cells making an organ, or the spatially-controlled growing of a plant, and to apply these principles to technological systems, in particular more intelligent and adaptable robot swarms.

The Project, with a 2,221,000€ budget, is funded by the European Comission under the 7th Framework Programme and will be performed by researchers in Spain, United Kingdom and the Netherlands.

Compared to human-made technology, living organisms have an enviable ability to adjust to new situations, make complex decisions, and even to heal themselves when damaged. By contrast, technological systems struggle to cope with the unexpected. An important example of such clever biology is multicellular organisation. The millions of cells, which make up an early embryo, can communicate only with their neighbours, and yet they are each capable of making the right decisions so that together they collaborate to build organs and whole bodies. Understanding how they achieve this will not only benefit biomedical research, but could also help us to build more intelligent technology.

The SWAM-ORGAN project focuses on systems containing large numbers of autonomous but relatively simple agents, whose goal is to collectively organise themselves into complex spatial arrangements despite each agent having only local awareness. They form complex patterns and deal with conflict or damage by acting locally but for the benefit of the whole. "Although we originally came from the biological questions of embryo development, I've been increasingly fascinated by the potential similarities between multicellular organs, and robot swarms" explained James Sharpe, the coordinator of the project. "The plan is that this project will be equally relevant to both fields, by focusing on the underlying organisational principles."

The goal of the project is to identify the principles of these systems and use them to design a theoretical framework about distributed adaptive control. The researchers will explore a specific approach, the gene regulatory networks, as a potentially powerful control method for these systems. Comparing networks between different biological processes, they will be able to identify patterns and fundamental principles that can be applied to technology.

The project is coordinated by ICREA Research Professor James Sharpe, acting coordinator of the Systems Biology Programme at the Centre for Genomic Regulation (CRG) in Barcelona (Spain). The research partners are Prof. Yaochu Jin, University of Surrey (United Kingdom), Dr. Jaap Kaandorp, Universiteit van Amsterdam (Netherlands) and Dr. Veronica Grieneisen, John Innes Centre (United Kingdom).


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Materials provided by Centre for Genomic Regulation. Note: Content may be edited for style and length.


Cite This Page:

Centre for Genomic Regulation. "From complex living systems to smarter computers." ScienceDaily. ScienceDaily, 19 March 2013. <www.sciencedaily.com/releases/2013/03/130319202038.htm>.
Centre for Genomic Regulation. (2013, March 19). From complex living systems to smarter computers. ScienceDaily. Retrieved April 25, 2024 from www.sciencedaily.com/releases/2013/03/130319202038.htm
Centre for Genomic Regulation. "From complex living systems to smarter computers." ScienceDaily. www.sciencedaily.com/releases/2013/03/130319202038.htm (accessed April 25, 2024).

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