title: Turing on Super-Turing and adaptivity.
abstract: Biological processes are often compared to computation and modeled on the Universal Turing Machine. While many systems or aspects of systems can be well described in this manner, Turing computation can only compute what it has been programmed for. It has no ability to learn or adapt to new situations. Yet, adaptation, choice and learning are all hallmarks of living organisms. This suggests that there must be a different form of computation capable of this sort of calculation. It also suggests that there are current computational models of biological systems that may be fundamentally incorrect. We argue that the Super-Turing model is both capable of modeling adaptive computation, and furthermore, a possible answer to the computational model searched for by Turing himself.
authors.affiliation: BINDS lab, Dept. of Computer Science, Prog. of Neuroscience and Behavior, UMass Amherst, Amherst, MA 01002, United States. Electronic address: hava@cs.umass.edu.
authors.forename: Hava T
authors.initials: HT
authors.lastname: Siegelmann
mesh_terms: D000222:Adaptation, Physiological / Q000502:physiology*; D000465:Algorithms; D001185:Artificial Intelligence; D001703:Biophysics / Q000379:methods; D003198:Computer Simulation; D005246:Feedback; D008433:Mathematics; D008954:Models, Biological; D008967:Molecular Biology / Q000379:methods; D049490:Systems Biology / Q000379:methods*; D018511:Systems Integration
keywords: Adaptive computation; Biological computation; Super-Turing computation