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SELECTIVE PRESSURES. “The genetic code is not quite universal. The rare variations that we know of reveal selective pressures on the code and on the translation machinery. New data suggest the code changes through ambiguous intermediates and that termination is context dependent.“ https://www.sciencedirect.com/science/article/pii/S0960982216309174 View in LinkedIn

SELECTIVE PRESSURES. “The genetic code is not quite universal. The rare variations that we know of reveal selective pressures on the code and on the translation machinery. New data suggest the code changes through ambiguous intermediates and that termination is context dependent.“ https://www.sciencedirect.com/science/article/pii/S0960982216309174 View in LinkedIn

SECONDARY VARIATIONS. “The standard genetic code is virtually universal among extant life forms. Although many deviations from the universal code exist, particularly in organelles and prokaryotes with small genomes, they are limited in scope and obviously secondary.” https://lnkd.in/ddaxciH View in LinkedIn

NOT OPTIMAL. “However, the standard genetic code is far from being optimal because, given the enormous overall number of possible codes (>10(84)), billions of variants are even more robust to error.” http://www.mdpi.com/2075-1729/7/2/22/htm View in LinkedIn

HIGH FIDELITY. “Quantitative analyses of the code using cost functions derived from physico-chemical properties of amino acids or their evolutionary exchangeability have confirmed the exceptional robustness of the standard genetic code: the probability to reach the same level of error minimization as in the standard genetic code by random permutation of codons is below 10(-6).” http://www.mdpi.com/2075-1729/7/2/22/htm View in LinkedIn

ECOSYSTEMS. "Genetic programming, autonomous agents, artificial life and evolutionary computation share many common ideas. They generally investigate distributed complex processes, perhaps with the ability to interact." https://lnkd.in/dBswHTH View in LinkedIn

MOLECULAR EVOLUTION is a topic on its own. But how evolving molecules crossed the line to give rise to complex organizations that were self-reproducing, capable of evolving, and accrued intelligence is another issue. Both topics are at the heart of biology, but our understanding of them is slight to non-existent. View in LinkedIn

"GENETIC PROGRAMMING (GP) is method for automatically creating computer programs. It starts from a high-level statement of what needs to be done and uses the Darwinian principle of natural selection to breed a population of improving programs over many generations." Not what it sounds like. https://lnkd.in/dhwv8HE View in LinkedIn

ANTICIPATION. "Such evolutionary prediction was motivated by a recognition that prediction is a keystone to intelligent behavior (defined in terms of adaptive behavior, in that the intelligent organism must anticipate events in order to adapt behavior in light of a goal)." http://www6.uniovi.es/ftp/pub/EC/FAQ/www/Q1_2.htm View in LinkedIn

SIMULATED EVOLUTION. "The 1966 book, "Artificial Intelligence Through Simulated Evolution" by Fogel, Owens and Walsh is the landmark publication for EP applications, although many other papers appear earlier in the literature. In the book, finite state automata were evolved to predict symbol strings generated from Markov processes and non-stationary time series." https://lnkd.in/eC54QCG View in LinkedIn