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language-evolution

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rkapur102 / language_phylogeny_feature_simulations

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Simulations of language evolution and phylogenetic/feature dynamics, as described in: "Kapur, Rhea and Phillip Rogers. 2020. Modeling language evolution and feature dynamics in a realistic geographic environment. 28th International Conference on Computational Linguistics (COLING 2020), Barcelona, Spain."

language-modeling data-analysis dispersion computational-linguistics descriptive-statistics phylogeny language-evolution feature-dynamics simulated-families populated-places glottolog-data wals-data
  • Updated Nov 2, 2020
  • R

TGDivy / Language-Evolution

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We use reinforcement learning to study how language can be used as a tool for agents to accomplish tasks in their environment, and show that structure in the evolved language emerges naturally through iterated learning, leading to the development of compositional language for describing and generalising about unseen objects.

reinforcement-learning natural-language-generation pomdp wordembeddings multiagent-reinforcement-learning language-evolution iterated-learning ppo student-teacher-learning
  • Updated Jan 7, 2023
  • Python

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