title: Symbolic representation of probabilistic worlds.
abstract: Symbolic representation of environmental variables is a ubiquitous and often debated component of cognitive science. Yet notwithstanding centuries of philosophical discussion, the efficacy, scope, and validity of such representation has rarely been given direct consideration from a mathematical point of view. This paper introduces a quantitative measure of the effectiveness of symbolic representation, and develops formal constraints under which such representation is in fact warranted. The effectiveness of symbolic representation hinges on the probabilistic structure of the environment that is to be represented. For arbitrary probability distributions (i.e., environments), symbolic representation is generally not warranted. But in modal environments, defined here as those that consist of mixtures of component distributions that are narrow ("spiky") relative to their spreads, symbolic representation can be shown to represent the environment with a relatively negligible loss of information. Modal environments support propositional forms, logical relations, and other familiar features of symbolic representation. Hence the assumption that our environment is, in fact, modal is a key tacit assumption underlying the use of symbols in cognitive science.
authors.affiliation: Department of Psychology, Center for Cognitive Science, Rutgers University-New Brunswick, 152 Frelinghuysen Rd., Piscataway, NJ 08854, United States. jacob@ruccs.rutgers.edu
authors.forename: Jacob
authors.initials: J
authors.lastname: Feldman
mesh_terms: D000465:Algorithms; D003071:Cognition / Q000502:physiology*; D006801:Humans; D008128:Logic; D008606:Mental Processes / Q000502:physiology*; D008959:Models, Neurological; D015233:Models, Statistical