title: Evolutionary Design of Classifiers Made of Droplets Containing a Nonlinear Chemical Medium.
abstract: Unconventional computing devices operating on nonlinear chemical media offer an interesting alternative to standard, semiconductor-based computers. In this work we study in-silico a chemical medium composed of communicating droplets that functions as a database classifier. The droplet network can be "programmed" by an externally provided illumination pattern. The complex relationship between the illumination pattern and the droplet behavior makes manual programming hard. We introduce an evolutionary algorithm that automatically finds the optimal illumination pattern for a given classification problem. Notably, our approach does not require us to prespecify the signals that represent the output classes of the classification problem, which is achieved by using a fitness function that measures the mutual information between chemical oscillation patterns and desired output classes. We illustrate the feasibility of our approach in computer simulations by evolving droplet classifiers for three machine learning datasets. We demonstrate that the same medium composed of 25 droplets located on a square lattice can be successfully used for different classification tasks by applying different illumination patterns as its externally supplied program.
authors.affiliation: Department of Complex Systems, Institute of Physical Chemistry, Polish Academy of Sciences, Kasprzaka 44/52, 01-224 Warsaw, Poland kgizynski@ichf.edu.pl.
authors.forename: Konrad
authors.initials: K
authors.lastname: Gizynski
authors.affiliation: Bio Systems Analysis Group, Institute of Computer Science, Friedrich Schiller University Jena, 07743 Jena, Germany gerd.gruenert@uni-jena.de.
authors.forename: Gerd
authors.initials: G
authors.lastname: Gruenert
authors.affiliation: Bio Systems Analysis Group, Institute of Computer Science, Friedrich Schiller University Jena, 07743 Jena, Germany peter.dittrich@uni-jena.de.
authors.forename: Peter
authors.initials: P
authors.lastname: Dittrich
authors.affiliation: Department of Complex Systems, Institute of Physical Chemistry, Polish Academy of Sciences, Kasprzaka 44/52, 01-224 Warsaw, Poland jgorecki@ichf.edu.pl.
authors.forename: Jerzy
authors.initials: J
authors.lastname: Gorecki
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003201:Computers; D016571:Neural Networks, Computer; D012666:Semiconductors
keywords: Unconventional computation; classification; droplet; evolutionary computation; information–theory-based fitness; mutual information; photosensitive Belousov–Zhabotinsky reaction