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Minimax featural computation in mathematical biolinguistics

数学生物语言学中的极小极大特征计算

基本信息

批准号：
2607680
负责人：
金额：
--
依托单位：
University of Cambridge
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2021
资助国家：
英国
起止时间：
2021 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2607680
关键词：
Minimax featural computation mathematical biolinguistics

项目摘要

My research proposal stems from the 'weak AI/strong AI' debate evident in Max Tegmark's work but ultimately stemmingfrom the work of Alan Turing. My summer project countenanced this problem in the domain of phonology, closelyfollowing Hale & Reiss (2008) and their criticism of Optimality Theory. I wish to develop this into the domain of syntax,where the idea of being 'substance-free' is somewhat harder to avoid, especially in cartographic approaches whichincorporate a lot of semantic content into what should be syntactic features. The question posed in the Turing programfor linguistic theory is, then, to evaluate the extent to which current linguistic theories achieve the goal of stronggenerativity, and to improve formalisms as such. As my proposal details, I see this approach as having a lot to do withthe precise nature of features and how they combine. In this sense I diverge from Cedric Boeckx (2014), but I believethat further investigation will reveal important overlap. On my view, this necessarily develops into a stronglyinterdisciplinary approach, in line with the biolinguistic programme. Such areas include mathematics (cf. Song's 2019dissertation on category theory), computer science (complexity theory), cognitive science (Poeppel; Gallistel & King) andbiological and evolutionary concerns (Boeckx; Balari & Lorenzo). The ambitious goal is to build a theory from the groundup which critically intertwines the essential aspects of these theories and disciplines.

我的研究建议源于Max Tegmark的研究中显而易见的“弱人工智能/强人工智能”的争论，但最终还是源于艾伦·图灵的研究。我的暑期项目在音系学领域支持了这个问题，紧跟着Hale&Reiss(2008)和他们对最优化理论的批评。我希望将这一点发展到句法领域，在句法领域，“无实质”的想法更难避免，特别是在制图方法中，这些方法将大量语义内容纳入到本应是句法特征的内容中。因此，在图灵语言理论纲领中提出的问题是，评估当前的语言理论在多大程度上实现了强生成性的目标，并改进了这种形式主义。正如我的提案细节所示，我认为这种方法与功能的确切性质以及它们的组合方式有很大关系。在这个意义上，我与塞德里克·博克斯(Cedric Boeckx，2014)有所不同，但我相信，进一步的研究将揭示重要的重叠。我认为，根据生物语言学计划，这必然会发展成为一种强有力的跨学科方法。这些领域包括数学(参见宋的2019年关于范畴理论的论文)、计算机科学(复杂性理论)、认知科学(Poeppel；Gallistel&King)以及生物学和进化关注(Boeckx；Balari&Lorenzo)。雄心勃勃的目标是从Ground Up建立一个理论，它批判性地将这些理论和学科的基本方面交织在一起。