How groups develop a specialized domain vocabulary: A cognitive multi-agent model

David Reitter, Christian Lebiere

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


We simulate the evolution of a domain vocabulary in small communities. Empirical data show that human communicators can evolve graphical languages quickly in a constrained task (Pictionary), and that communities converge towards a common language. We propose that simulations of such cultural evolution incorporate properties of human memory (cue-based retrieval, learning, decay). A cognitive model is described that encodes abstract concepts with small sets of concrete, related concepts (directing), and that also decodes such signs (matching). Learning captures conventionalized signs. Relatedness of concepts is characterized by a mixture of shared and individual knowledge, which we sample from a text corpus. Simulations show vocabulary convergence of agent communities of varied structure, but idiosyncrasy in vocabularies of each dyad of models. Convergence is weakened when agents do not alternate between encoding and decoding, predicting the necessity of bi-directional communication. Convergence is improved by explicit feedback about communicative success. We hypothesize that humans seek out subtle clues to gauge success in order to guide their vocabulary acquisition.

Original languageEnglish (US)
Pages (from-to)175-185
Number of pages11
JournalCognitive Systems Research
Issue number2
StatePublished - Jun 2011

All Science Journal Classification (ASJC) codes

  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience
  • Artificial Intelligence


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