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Dynamic control and information processing in the Belousov-Zhabotinsky reaction using a coevolutionary algorithm (2008)
Journal Article
Toth, R., Stone, C., Adamatzky, A., De Lacy Costello, B., & Bull, L. (2008). Dynamic control and information processing in the Belousov-Zhabotinsky reaction using a coevolutionary algorithm. Journal of Chemical Physics, 129(18), 184708. https://doi.org/10.1063/1.2932252

We propose that the behavior of nonlinear media can be controlled dynamically through coevolutionary systems. In this study, a light-sensitive subexcitable Belousov-Zhabotinsky reaction is controlled using a heterogeneous cellular automaton. A checke... Read More about Dynamic control and information processing in the Belousov-Zhabotinsky reaction using a coevolutionary algorithm.

Evolving localizations in reaction-diffusion cellular automata (2008)
Journal Article
Adamatzky, A., Bull, L., Collet, P., & Sapin, E. (2008). Evolving localizations in reaction-diffusion cellular automata. International Journal of Modern Physics C, 19(04), 557-567. https://doi.org/10.1142/S0129183108012376

We consider hexagonal cellular automata with immediate cell neighbourhood and three cell-states. Every cell calculates its next state depending on the integral representation of states in its neighbourhood, i.e., how many neighbours are in each one s... Read More about Evolving localizations in reaction-diffusion cellular automata.

Towards unconventional computing through simulated evolution: Control of nonlinear media by a learning classifier system (2008)
Journal Article
Bull, L., Budd, A., Stone, C., Uroukov, I., Costello, B. D. L., & Adamatzky, A. (2008). Towards unconventional computing through simulated evolution: Control of nonlinear media by a learning classifier system. Artificial Life, 14(2), 203-222. https://doi.org/10.1162/artl.2008.14.2.203

We propose that the behavior of nonlinear media can be controlled automatically through evolutionary learning. By extension, forms of unconventional computing (viz., massively parallel nonlinear computers) can be realized by such an approach. In this... Read More about Towards unconventional computing through simulated evolution: Control of nonlinear media by a learning classifier system.

Initial results from the use of evolutionary learning to control chemical computers (2008)
Journal Article
Budd, A., Stone, C., Masere, J., Adamatzky, A., de Lacy Costello, B., & Bull, L. (2008). Initial results from the use of evolutionary learning to control chemical computers. International Journal of Unconventional Computing, 4(1), 13-22

The behaviour of pulses of Belousov-Zhabotinski (BZ) reaction diffusion waves can be controlled automatically through machine learning. By extension, a form of chemical network computing, i.e., a massively parallel non-linear Computer, can be realise... Read More about Initial results from the use of evolutionary learning to control chemical computers.