Evolution of communication using symbol combination in populations of neural networks

Abstract

This paper uses a model of neural network and genetic algorithms to simulate the evolution of communication in populations of evolving neural networks. It focuses on the emergence of simple forms of syntax, i.e., the combination of two symbols. The simulation task resembles Savage-Rumbaugh and Rumbaugh's experiment (1978) on ape language and symbol acquisition. The simulation results show the evolution and cultural transmission of languages based on combination of grounded symbols. The model is analyzed according to the issues of the symbol grounding and symbol acquisition problems.