Creative information processing systems based on non-standard computation toward brain potentiality

基于非标准脑潜能计算的创意信息处理系统

基本信息

批准号：
16500135
负责人：
MATSUI Nobuyuki
金额：
$ 2.3万
依托单位：
University of Hyogo
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2004
资助国家：
日本
起止时间：
2004 至 2006
项目状态：
已结题

项目摘要

In this research, we tried to find the methods of creative thinking based on non-standard computation toward brain potentiality such as perceptual alternation phenomena and investigated the emergence of this creative effect through system applications to these methods. In our study of the creative information processing systems, we have obtained the following main results:1. We found the multiplet as the characteristics of association in discrete states and discrete time Hopfield neural network described by quaternion.2. We confirmed the efficiency of the qubit neural network in the color night vision and data-mining applications.3. We developed the block learning SOM system with high adaptability under non-stationary environments.4. We cleared the efficiency of the multi-stable perception model by multi-layered bi-directional associative memory.5. We derived flocking behaviors of agents from a scheme of reinforcement learning, and also clarified the effect of reinforcement learning using chaotic exploration in the maze world problem.6. We constructed the algorithms on defect-tolerance in the asynchronous cellular automaton and showed that defective cells are detected and isolated by configurations of random flies that move around in cellular space.As a result, we clarified that our creative information processing systems have better performances than conventional ones in processing various problems. We have presented a lot of our fruitful results so that we consider our research aims have been achieved. However, many subjects remain to be explored, for examples, Clifford algebra approach, Bloch representation on qubit neuron state and its application to cellular neural network, etc. These are our future works.

在这项研究中，我们试图基于对大脑潜力的非标准计算（例如感知交替现象）的非标准思维方法，并通过系统应用来调查了这种创造性效应的出现。在我们对创意信息处理系统的研究中，我们获得了以下主要结果：1。我们发现多重组是离散状态中的关联特征和Quaternion描述的离散时间Hopfield神经网络2。我们确认了量子神经网络在色彩夜视和数据挖掘应用程序中的效率3。我们在非平稳环境下开发了具有高适应性的块学习SOM系统4。我们通过多层双向关联内存清除了多稳定感知模型的效率。5。我们从增强学习方案中得出了代理的蜂拥而至的行为，还阐明了在迷宫世界问题中使用混乱探索的增强学习的效果。6。我们在异步细胞自动机中构建了易耐受性的算法，并表明通过在细胞空间中移动的随机蝇的构型检测和隔离了有缺陷的细胞。结果，我们澄清说，我们的创意信息处理系统比在处理各种问题中的常规性能更好。我们已经提出了许多富有成果的结果，因此我们认为我们的研究目标已经实现。但是，许多受试者仍有待探索，例如，Clifford代数方法，Qubit神经元状态的Bloch表示以及其在细胞神经网络中的应用等。这是我们的未来作品。