Attractor Selection Algorithm

Attractor Selection Algorithm is inspired by the adaptive behaviour of the E. coli cells.
Updated 3 Aug 2016

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As the basic functional unit of life, cells are biologically simple structures. Even so, as an outcome of billions of years of natural evolution, cells have come to possess some appealing biological characteristics, enabling them to be resilient to external damage and robust against biological noises, to adapt to varying environmental conditions and to infer their environmental state to make smart decisions. In addition, fully-distributed autonomy and self-organisation can also emerge from the simple-rules-based interactions of populations of cells, which allows them to utilise constrained environmental resources with high efficiency, in order to co-exist and co-evolve.
A biological mechanism intrinsic to the adaptive behaviour of the Escherichia coli (E. coli) cells known as attractor selection, which can induce the cellular gene network to dynamically accommodate its genetic programs to changes in environmental conditions. E. coli cells usually prefer to switch to a stable genetic program, i.e. selecting an adaptive attractor, so as to survive better (yielding a better metabolic phenotype) in a new external environment after the environmental conditions (such as nutrients) have been changed. This attractor selection mechanism has inspired simple robust and distributed solutions.
From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks. Scientific Reports, 6, 23048; doi: 10.1038/srep23048 (2016)
A Dynamic and Self-adaptive Network Selection Method for Multi-mode Communications in Heterogeneous Vehicular Telematics. IEEE Transactions on Intelligent Transportation Systems, 2015, Volume 16, Issue 6, pp.3033-3049.

Cite As

Daxin Tian (2024). Attractor Selection Algorithm (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2015b
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