Multi-agent language coordination and cognition v/ Nina Gierasimczuk
Natural languages vary in their quantity expressions, but the variation seems to be constrained by general properties, so-called universals. Explanations thereof have been sought among constraints of human cognition, communication, complexity, and pragmatics. In this work, we examine whether the perceptual constraints of approximate number sense (ANS) contribute to the development of two universals in the semantic domain of quantities: monotonicity and convexity. Using a state-of-the-art multi-agent language coordination model (originally applied to colour terms) we evolve communicatively usable quantity terminologies. We compare the degrees of convexity and monotonicity of languages evolvingin populations of agents with and without ANS. The results suggest that ANS supports the development of monotonicity and, to a lesser extent, convexity.