Agent-Based Simulation Models How Irregular Verb Forms Like 'Go/Went' Emerge and Persist in Languages
Computational linguists have developed a multi-agent simulation system to model how morphological alternations — such as the English past tense 'went' for 'go' — emerge and persist in language populations. The study combines agent-based modeling with realistic phonological rules and large lexicons, and introduces an LLM-driven 'AI Historical Linguist' to evaluate how plausible the simulated morphologies are compared to real languages. The findings suggest that scale-free social networks and random Bernoulli adoption policies produce the most naturalistic-looking morphological patterns.
A new preprint from arXiv introduces a multi-agent computational framework designed to simulate the emergence and entrenchment of morphological stem and inflection alternations in language — phenomena like the suppletive English past tense 'went' for 'go.' In the model, agents hear novel word forms used by others and probabilistically adopt them, potentially spreading changes across related slots in a word's paradigm. Unlike prior computational studies, the system supports naturalistic lexical forms, realistic phonological rules, lexicons of hundreds to thousands of entries, and agent populations in the tens to hundreds, as well as multiple network topologies and diffusion patterns. To evaluate realism, the authors introduce the 'AI Historical Linguist,' a novel system that uses a large language model to simulate a debate between two historical linguists assessing real, disguised, and experimentally evolved morphologies. Results indicate that scale-free social networks and random Bernoulli adoption of forms yield the most plausible morphological outcomes. The paper also presents three case studies modeling attested historical linguistic changes, exploring counterfactual scenarios about what might have occurred under different conditions. All code and data have been released publicly.
What's missing
The LLM-based evaluation method ('AI Historical Linguist') is novel and its reliability as a proxy for expert linguistic judgment has not been independently validated.
What different sources said
- arXiv cs.CLCenter
Agent-based models for the evolution of morphological alternation patterns
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