CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
The emergence of linguistic structure: an overview of the iterated learning model
Simulating the evolution of language
Grounding symbols through evolutionary language games
Simulating the evolution of language
Iterated learning: a framework for the emergence of language
Artificial Life
The emergence of compositional structures in perceptually grounded language games
Artificial Intelligence - Special volume on connecting language to the world
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We investigate the properties of coupled co-learning systems during the emergence of communication. Co-learning systems are more complex than individual learning systems because of being dependent on the learning process of each other, thus risking divergence. We developed a neural network approach and implemented a concept that we call reconstruction principle, which we found adequate for overcoming the instability problem. Experimental simulations were performed to test the emergence of both compositional and holistic communication. The results show that compositional communication is favorable when learning performance is considered, however it is more error-prone to differences in the conceptual representations of the individual systems. We show that our architecture enables the adjustment of the differences in the individual representations in case of compositional communication.