Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10884688 | Biosystems | 2005 | 19 Pages |
Abstract
The expressiveness of evolutionary computation is investigated. We show that the problem of the best evolutionary algorithm is undecidable independently of whether the fitness function is time dependent or fixed. It is demonstrated that the evolutionary computation paradigm is more expressive than Turing Machines, and thus the conventional computer science based on them. We show that an Evolutionary Turing Machine is able to solve nonalgorithmically the halting problem of the Universal Turing Machine and, asymptotically, the best evolutionary algorithm problem. In other words, the best evolutionary algorithm does not exist, but it can be potentially indefinitely approximated using evolutionary techniques.
Related Topics
Physical Sciences and Engineering
Mathematics
Modelling and Simulation
Authors
Eugene Eberbach,