Conceptual Spaces: The Geometry of Thought
Conceptual Spaces: The Geometry of Thought
Self-Organizing Maps
Establishing Communication Systems without Explicit Meaning Transmission
ECAL '01 Proceedings of the 6th European Conference on Advances in Artificial Life
Learning robot actions based on self-organising language memory
Neural Networks - 2003 Special issue: Advances in neural networks research IJCNN'03
The emergence of compositional structures in perceptually grounded language games
Artificial Intelligence - Special volume on connecting language to the world
IEEE Transactions on Evolutionary Computation
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In this article, we study the emergence of associations between words and concepts using the self-organizing map. In particular, we explore the meaning negotiations among communicating agents. The self-organizing map is used as a model of an agent's conceptual memory. The concepts are not explicitly given but they are learned by the agent in an unsupervised manner. Concepts are viewed as areas formed in a self-organizing map based on unsupervised learning. The language acquisition process is modeled in a population of simulated agents by using a series of language games, specifically observational games. The results of the simulation experiments verify that the agents learn to communicate successfully and a shared lexicon emerges.