is0383kk/SymbolEmergence-VAE-GMM
Symbol emergence using Variational Auto-Encoder and Gaussian Mixture Model (Inter-GMM-VAE)~VAEを活用した実画像からの記号創発~
This project explores how two AI agents can develop a shared understanding or 'language' for images through a "naming game." Each agent observes images independently and learns to categorize them. Through communication, where they propose and accept/reject each other's image categories, they collaboratively refine their understanding until their categories align. This is useful for researchers studying artificial intelligence, cognitive science, and machine learning interested in how shared meaning emerges in multi-agent systems.
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Use this if you are a researcher in AI or cognitive science interested in the computational modeling of emergent communication and shared symbol grounding between artificial agents.
Not ideal if you are looking for a ready-to-use image classification tool or a system that communicates in natural language.
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Language
Python
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CC-BY-SA-4.0
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Last pushed
Oct 08, 2025
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