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Structural Inductive Biases in Emergent Communication

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 نشر من قبل Abhinav Gupta
 تاريخ النشر 2020
  مجال البحث الهندسة المعلوماتية
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In order to communicate, humans flatten a complex representation of ideas and their attributes into a single word or a sentence. We investigate the impact of representation learning in artificial agents by developing graph referential games. We empirically show that agents parametrized by graph neural networks develop a more compositional language compared to bag-of-words and sequence models, which allows them to systematically generalize to new combinations of familiar features.



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