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The principle of computational equivalence says that “systems found in the natural world can perform computations up to a maximal ("universal") level of computational power, and that most systems do in fact attain this maximal level of computational power.” | The principle of computational equivalence says that “systems found in the natural world can perform computations up to a maximal ("universal") level of computational power, and that most systems do in fact attain this maximal level of computational power.” | ||
The structure of a system need not be complicated for its behavior to be highly complex. Cellular Automata (e.g rule 30) can provide an example to provide models for a wide variety of complex | The structure of a system need not be complicated for its behavior to be highly complex. Cellular Automata (e.g rule 30) can provide an example to provide models for a wide variety of complex systems. Even Turing machine model with one cell updating would be a model for complex behaviors. Universal machines that can do any kind of computations have many implications for natural science too. It is easy to see the reflections of the Computational Equivalence Principle in Richard Dawkins Biomorphosis, Thomas Ray’s Tierra project, and Karl Sim’s virtual creatures. | ||
It is easy to see the reflections of the Computational Equivalence Principle in Richard Dawkins Biomorphosis, Thomas Ray’s Tierra project, and Karl Sim’s virtual creatures. | |||
I always have an impression that everything in the universe is too complicated and doesn’t give too much chance to be computed. Evolutionary biologist Thomas Ray makes a comparison as the genetic language consists of an alphabet of 20 letters and a computer language has many. He takes inspiration from natural science and uses computer science to solve problems. Not only algorithms, but he also distinguishes the inside of a computer as a physical system by making an analogy of the sun, the source of energy, as CPU and creatures living in the memory. This also supports Wolfram’s idea of a close correspondence between physical processes and computations. Like the Computational Equivalence principle, Thomas Ray seems to build very complex ecological phenomena with his very simplified computer program. | I always have an impression that everything in the universe is too complicated and doesn’t give too much chance to be computed. Evolutionary biologist Thomas Ray makes a comparison as the genetic language consists of an alphabet of 20 letters and a computer language has many. He takes inspiration from natural science and uses computer science to solve problems. Not only algorithms, but he also distinguishes the inside of a computer as a physical system by making an analogy of the sun, the source of energy, as CPU and creatures living in the memory. This also supports Wolfram’s idea of a close correspondence between physical processes and computations. Like the Computational Equivalence principle, Thomas Ray seems to build very complex ecological phenomena with his very simplified computer program. | ||