Understanding Quantifiers in Language
Jakub Szymanik, Marcin Zajenkowski

Abstract:
We investigate the comprehension of simple quantifiers in natural
language as described in a computational model posited by many
linguists and logicians. In particular, we compare time needed for
understanding different types of quantifiers. We show that the
computational distinction between quantifiers recognized by
finite-automata and push-down automata is psychologically
relevant. Our research improves upon hypothesis and explanatory power
of recent neuroimaging studies as well as provides evidence for the
claim that human linguistic abilities are constrained by computational
complexity.