Second order learning and the evolution of mental representation

Abstract

Mental representation is a fundamental aspect of advanced cognition. An understanding of the evolution of mental representation is essential to an understanding of the evolution of mind. However, being a decidedly mental phenomenon, its evolution is difficult to study. We hypothesize how interactions between adaptation levels may cause emergence of isomorphism between a cognitive system and its environment, and that mental representation may be understood as an instance of this effect. Specifically, we propose that selection for second order learning translates into selection for isomorphism-based implementation of first order learning ability, and that mental representation is (an aspect of) the environment-cognition isomorphism produced by such learning ability. We then give a reformulation of cognitive map ability, a paradigm case of mental representation, in terms of our hypothesis and explore it computationally by evolving a neural network species with the neural basics for second order plasticity (the basis for second order learning) in an environment composed of randomly generated maze tasks, including tasks generally believed to require mental representation (in the form of cognitive maps). The model is shown capable of evolving nets that solve these tasks, providing preliminary support for our hypothesis. © 2012 Massachusetts Institute of Technology.