Editing Evolutionary computation (section)

=== Evolutionary algorithms and biology ===
{{Main|Evolutionary algorithm}}

[[Genetic algorithms]] deliver methods to model [[biological systems]] and [[systems biology]] that are linked to the theory of [[dynamical systems]], since they are used to predict the future states of the system. This is just a vivid (but perhaps misleading) way of drawing attention to the orderly, well-controlled and highly structured character of development in biology.

However, the use of algorithms and informatics, in particular of [[computational theory]], beyond the analogy to dynamical systems, is also relevant to understand evolution itself.

This view has the merit of recognizing that there is no central control of development; organisms develop as a result of local interactions within and between cells. The most promising ideas about program-development parallels seem to us to be ones that point to an apparently close analogy between processes within cells, and the low-level operation of modern computers.<ref>{{Cite book | chapter-url=https://plato.stanford.edu/entries/information-biological/#InfEvo | title=The Stanford Encyclopedia of Philosophy| chapter=Biological Information| publisher=Metaphysics Research Lab, Stanford University| year=2016}}</ref> Thus, biological systems are like computational machines that process input information to compute next states, such that biological systems are closer to a computation than classical dynamical system.<ref>{{cite journal |author= J.G. Diaz Ochoa |title= Elastic Multi-scale Mechanisms: Computation and Biological Evolution |journal=[[Journal of Molecular Evolution]] |volume=86 |issue=1 |pages=47–57 |year=2018 |pmid=29248946 |doi=10.1007/s00239-017-9823-7 |bibcode=2018JMolE..86...47D |s2cid= 22624633 }}</ref>

Furthermore, following concepts from [[computational theory]], micro processes in biological organisms are fundamentally incomplete and undecidable ([[completeness (logic)]]), implying that “there is more than a crude metaphor behind the analogy between cells and computers.<ref>{{cite journal |author= A. Danchin |title= Bacteria as computers making computers |journal=[[FEMS Microbiol. Rev.]] |volume=33 |issue=1 |pages=3–26 |year=2008 |doi=10.1111/j.1574-6976.2008.00137.x |pmid= 19016882 |pmc=2704931 }}</ref>

The analogy to computation extends also to the relationship between [[inheritance systems]] and biological structure, which is often thought to reveal one of the most pressing problems in explaining the origins of life.

''Evolutionary automata''{{r|ldr11|ldr13|ldr14}}, a generalization of ''Evolutionary Turing machines''{{r|ldr15|ldr16}}, have been introduced in order to investigate more precisely properties of biological and evolutionary computation. In particular, they allow to obtain new results on expressiveness of evolutionary computation{{r|ldr14|ldr17}}. This confirms the initial result about undecidability of natural evolution and evolutionary algorithms and processes. ''Evolutionary finite automata'', the simplest subclass of Evolutionary automata working in ''terminal mode'' can accept arbitrary languages over a given alphabet, including non-recursively enumerable (e.g., diagonalization language) and recursively enumerable but not recursive languages (e.g., language of the universal Turing machine){{r|ldr18}}.