文摘
Using an agent based model, we investigate stable irregularity in a language system. A population of interacting agents evolve shared rules and exceptions. Without specific agent biases, irregularity is dependent on initial conditions. We implement two types of biases in agents: learner biases and memory constraints. Biases lead to stable irregularity reminiscent of patterns found in natural language.