Construction of an Optimality-Theoretic Theory of Case and Linking and Its Realization on a Neural Network

今年的研究目的是为将具有反向传播学习算法的多层感知器转换为采用我们大脑中使用的Hebbian学习算法的神经网络提供基础，该算法实现了宾格/作格系统。具体地说，ER发表并撰写了一篇论文，研究了量子神经网络的计算能力(参见MatSumoto、Okubo和Nishino 2004)。量子神经网络的强大计算能力能否应用于模拟语言习得过程的神经网络。我们无法在神经网络上模拟后动词岛阶段，但我们正在研究如何模拟英语和日语中发现的宾语连接系统的习得过程，假设NP、VP或AP等句法范畴是先天的。具体地说，我们正在计划构建一个神经网络，它基于Danry(1995)和Ackerman and Moore(2003)的原型理论提出的一系列语义特征来获取语法关系的宾语系统。最后，我们使用功能脑成像技术考察了人脑如何理解主动/被动句，尤其是如何理解日语(见Yokyama，Uchida，Nakamura，Kawashima等人，2004)。日语或英语句子。

The aim of this year's study was to provide a foundation for transforming a mufti-layered perceptron with a back propagation learning algorithm which realizes an accusative/ergative case system into a neural neywork which adopts a Hebbian learning algorithm as used in our brain. Specifically, er presented and wrote a paper which examined the computational capabilities of a quantum neural network (see Matsumoto, Okubo, and Nishino 2004). This work investigated whether it is possible to apply a very powerful computational capability of a quantum neural network to neuroidal network which is is designed to simulate the process of language acquisition.We were not able to simulate a post-'Verb Island' phase on a neuroidal network, but we are in the process of investigating how to simulate the process of acquiring an accusative linking system as found in English and Japanese under the assumption that syntactic categories such as NP, VP, or AP are innate. Specifically, we are planning to construct a neuroidal network which acquires an accusative system of grammatical relations on the basis of a bundle of semantic features as proposed by Dowry's (1995) and Ackerman and Moore's (2003) protorole theory.Finally, we examined how the human brain comprehends an active/passive sentence, using the functional brain imaging with a particular focus on how Japanese understands (see Yokoyama., Uchida, Nakamura, Kawashima, and others 2004). a Japanese or English sentence.