Cooperative information control and second language learning: a new information theoretic approach to self-organizing maps

Abstract

We propose an information theoretic approach called cooperative information control. The new method realizes self-organizing maps in a way completely different from the conventional SOM. In addition, the method can create clearer neuron firing patterns. In the method, competition is realized by maximizing information content in neurons. Cooperation is implemented by having neurons behave similarly to their neighbors. These two processes are unified and controlled in the framework of cooperative information control. We applied the new method to applied linguistic data analysis. Experimental results confirmed that the method can yield more explicit neuron firing patterns than the conventional self-organizing maps.