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'''Principle of Computational Equivalence''' | '''Principle of Computational Equivalence''' | ||
Can simple programs produce very rich and complicated behaviors? Could it be possible that all of the amazing things we see in the universe be the result of a simple program? That would be very exciting to have a program that is an ultimate precise model of our universe. If you run it long enough it would produce complex models. Stephen Wolfram asks how would this program be like. | Can simple programs produce very rich and complicated behaviors? Could it be possible that all of the amazing things we see in the universe be the result of a simple program? That would be very exciting to have a program that is an ultimate precise model of our universe. If you run it long enough it would produce complex models. Stephen Wolfram asks how would this program be like. | ||
Revision as of 00:48, 8 December 2020
Principle of Computational Equivalence
Can simple programs produce very rich and complicated behaviors? Could it be possible that all of the amazing things we see in the universe be the result of a simple program? That would be very exciting to have a program that is an ultimate precise model of our universe. If you run it long enough it would produce complex models. Stephen Wolfram asks how would this program be like.
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 natural 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.
I always have an impression that everything in the universe is too complicated and doesn’t give too much chance to compute. Evolutionary biologist Thomas Ray makes this 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.
(will be updated...)