Simulation of language evolution using Fuzzy Grammars

Many computer simulations try to explain language evolution with socially oriented scenarios in multi-agent systems by applying methods such as genetic algorithms and neural networks. In this paper a new approach based on modifications to the classic Ant Colony Optimization algorithm is proposed. Ants are provided with a Fuzzy Grammar and the ability to embed a message in the pheromone. By fuzzifying the grammar, ants are able to modify the degree of membership of the production rules to gradually adopt a foreign language.