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Coevolving cellular automata with memory for chemical computing: Boolean logic gates in the BZ reaction (2008)
Book Chapter
Stone, C., Toth, R., de Lacy Costello, B., Bull, L., & Adamatzky, A. (2008). Coevolving cellular automata with memory for chemical computing: Boolean logic gates in the BZ reaction. In G. Rudolph, T. Jansen, S. M. Lucas, C. Poloni, & N. Beume (Eds.), Parallel Problem Solving from Nature - PPSN X: 10th International Conference Dortmund, Germany, September 13-17, 2008 (579-588). Berlin/Heidelberg: Springer

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.

Non-linear media based computers: chemical and neuronal networks through machine learning (2008)
Report
Bull, L., Adamatzky, A., de Lacy Costello, B., Husbands, P., O’Shea, M., Purcell, W., & Taylor, A. (2008). Non-linear media based computers: chemical and neuronal networks through machine learning

There is growing interest in research into the development of hybrid wetware-silicon devices focused on exploiting their potential for 'non-linear computing'. The aim is to harness the as yet only partially understood intricate dynamics of non-linear... Read More about Non-linear media based computers: chemical and neuronal networks through machine learning.

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.

Unconventional computing 2007 (2007)
Book
Adamatzky, A., de Lacy Costello, B., Bull, L., Stepney, S., & Teuscher, C. (2007). Unconventional computing 2007. Frome: Luniver Press