a Methodology for Learning Symbols in an Artificial Ecosystem

Abstract

We have modeled an artificial prey-predator ecosystem and proposed a methodology for learning a symbolic language in preys, so that it can generate an appropriate escaping behavior related to each predator after hearing the symbol of that predator. We have used an associative memory, a neural network and finally an ensemble learning method, hybrid of the first two methods, to show a significant improvement in learning process.