Abstract
We present 14 challenging problems of evolutionary computation, most of them derived from unfinished research work of outstanding scientists such as Charles Darwin, John von Neumann, Anatol Rapaport, Claude Shannon, and Alan Turing. The problems have one common theme: Can we develop a unifying theory or computational model of organisms (natural and artificial) which combines the properties structure, function, development, and evolution? There exist theories for each property separately as well as for some combinations of two. But the combination of all four properties seems necessary for understanding living organisms or evolving automata. We discuss promising approaches which aim in this research direction. We propose stochastic methods as a foundation for a unifying theory.
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Mühlenbein, H. (2004). Towards A Theory of Organisms and Evolving Automata. In: Menon, A. (eds) Frontiers of Evolutionary Computation. Genetic Algorithms and Evolutionary Computation, vol 11. Springer, Boston, MA. https://doi.org/10.1007/1-4020-7782-3_1
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DOI: https://doi.org/10.1007/1-4020-7782-3_1
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