Abstract
There is one very popular topic – not only for scientists, but for the community as a whole. Can machines easily learn something, which is not part of their programs? Can the machines revolt? If we are thinking only simple programming like functional or imperative, it is hard to imagine. But there are different kinds of programming, like setting the base program and rules, and let the programs teach themselves. These are the principles are used in Artificial neural networks and in Genetic/Evolution programming. US scientists have proven the potential of degeneration in ANN. This topic is focusing on the Evolution programming and its Ethical Degeneration in a Simulated Environment.
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Brozek, J., Sotek, K. (2019). Genetic Algorithms and Their Ethical Degeneration in Simulated Environment. In: Ntalianis, K., Vachtsevanos, G., Borne, P., Croitoru, A. (eds) Applied Physics, System Science and Computers III. APSAC 2018. Lecture Notes in Electrical Engineering, vol 574 . Springer, Cham. https://doi.org/10.1007/978-3-030-21507-1_20
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DOI: https://doi.org/10.1007/978-3-030-21507-1_20
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