The field of Linguistics has long been interested in the verb meanings of intransitive verbs and their argument structure, specifically the breakdown of intransitive verbs into unaccusative and unergative verb types. Despite extensive research, a universally applicable explanation for this breakdown remains elusive due in part to the variability observed across languages. The diverse categories and exceptional outcomes from various paradigms across multiple languages have further complicated attempts to find a definitive understanding of unaccusativity. This dissertation seeks to contribute new insights into this longstanding problem, approaching it from the perspective of language acquisition. In this dissertation, I regard the unaccusativity of verbs as a continued learning outcome and frame the investigation of its determinants as a language acquisition problem. Through a series of computational and behavioral experiments, I have discovered several semantic and constructional factors that can lead to differential learning outcomes during children's acquisition of unaccusativity. Subsequently, I propose a statistical and probabilistic framework that integrates these factors, as well as their interaction, which collectively contribute to the process of categorizing intransitive verbs. The results of this categorization form a dynamic and multicategorical system. By introducing these influencing factors and regarding their relationship as probabilistic and statistical, this dissertation aims to shed light on the nature of unaccusativity and the ongoing debates surrounding it. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]