title: The evolution of understanding: a genetic algorithm model of the evolution of communication.
abstract: Much animal communication takes place via symbolic codes, where each symbol's meaning is fixed by convention only and not by intrinsic meaning. It is unclear how understanding can arise among individuals utilizing such arbitrary codes, and specifically, whether evolution unaided by individual learning is sufficient to produce such understanding. Using a genetic algorithm implemented on a computer, I demonstrate that a significant though imperfect level of understanding can be achieved by organisms through evolution alone. The population as a whole settles on one particular scheme of coding/decoding information (there are no separate dialects). Several features of such evolving systems are explored and it is shown that the system as a whole is stable against perturbation along many different kinds of ecological parameters.
authors.affiliation: Genetics Dept., Harvard Medical School, Boston, MA 02115, USA. mlevin@husc7.harvard.edu
authors.forename: M
authors.initials: M
authors.lastname: Levin
mesh_terms: D000465:Algorithms; D000819:Animal Communication; D000818:Animals; D005075:Biological Evolution; D017753:Ecosystem; D008957:Models, Genetic