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. Keywords: language comprehension; generalized quantifiers; finite- and push-down automata; computational semantics of natural language