The Problem of Learning the Semantics of Quantifiers
Nina Gierasimczuk

Abstract:
This paper is concerned with a possible mechanism for learning the
meanings of quantifiers in natural language. The meaning of a natural
language construction is identified with a procedure for recognizing
its extension. Therefore, acquisition of natural language quantifiers
is supposed to consist in collecting procedures for computing their
denotations.  A method for encoding classes of finite models
corresponding to given quantifiers is shown. The class of finite
models is represented by appropriate languages. Some facts describing
dependencies between classes of quantifiers and classes of devices are
presented. In the second part of the paper examples of syntax-learning
models are shown. According to these models new results in quantifier
learning are presented. Finally, the question of the adequacy of
syntax-learning tools for describing the process of semantic learning
is stated.