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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
Published on: February 3, 2023
Genetic biasing through cultural transmission: do simple Bayesian models of language evolution generalize?
1Max Planck Institute for Psycholinguistics, Wundtlaan 1, 6500 AH Nijmegen, The Netherlands. Dan.Dediu@mpi.nl
Journal of Theoretical Biology
|April 18, 2009
Summary
Bayesian models of language evolution show that complex populations, not just single learners, reveal how cultural transmission interacts with genetic biases. This challenges assumptions about children driving language change.
Area of Science:
- Computational linguistics
- Evolutionary biology
- Cognitive science
Background:
- Bayesian approaches model language evolution, considering genetic biases and cultural transmission.
- A key debate involves differences between sampling and maximizing Bayesian learners regarding language evolution freedom.
- Current models often use simplified single-teacher/learner chains, potentially limiting generalizability.
Purpose of the Study:
- To investigate how population complexity affects Bayesian models of language evolution.
- To reconcile differing predictions from sampling versus maximizing Bayesian learners.
- To assess the validity of the 'acquisitionist' assumption in language change.
Main Methods:
- Simulated populations with varying complexity (beyond single agent chains).
- Comparison of agent behaviors in 'sampling' versus 'maximizing' Bayesian learning models.
- Analysis of language evolution dynamics under different population structures.
Main Results:
- The difference between sampling and maximizing Bayesian learners diminishes in more complex populations.
- Agent behaviors in complex populations resemble those of 'samplers'.
- Generalizations from single-agent chain models may not accurately reflect language evolution.
Conclusions:
- Population structure significantly influences language evolution dynamics in Bayesian models.
- Findings question the reliability of models based on simplified agent interactions.
- Results cast doubt on the 'acquisitionist' view, suggesting adult language users may be more central to language change.
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