Study on Parallel Processing of Multimedia in AI Systems

为了给出人工智能(AI)系统框架内的多媒体信息并行处理技术，我们研究了该技术的要素。我们还增强了这些元素，如下所述。一种智能绘图算法和“感性”表达方法的研究我们为人工智能系统开发了理解、解释和表达多媒体信息的算法。然后，我们将这些算法分别与识别方法和归纳学习方法相结合，分别进行了研究。因此，组合算法实现了高级别的处理。我们还考察了它在艺术领域的‘感性’表达。音乐信息处理的研究我们开发了一个基于分形技术的音乐创作编排系统，并将其用于图像编码。然后，我们对该系统进行了增强，以便给出音乐的总体配置。增强后的系统不仅可以生成和表达主…更多的旋律，但也对应音乐的部分和音乐的其他部分，通过考虑音乐的结构。基于战略解决方法的问题解决方法研究我们发展了一种方法，用于归纳、概括和使用战略知识作为一般问题解决框架。在实际应用中对其效果进行了检验。我们还研究了进化方法中的另一种方法。将这两种方法结合起来，仍需在以后的工作中使用。基于并行归纳学习算法的知识获取我们研究了归纳学习方法在多媒体信息分类和解释中的应用。我们开发并比较了三种不同的方法来并行化学习方法。这项研究得出了一个公认的结果。我们需要开发进一步的增强功能以用于更大规模的应用程序。基于并行技术的高速溯因推理方法研究在溯因推理的框架内，我们开发了使用并行处理的加速技术。这是在由通过网络连接的许多计算机组成的实际环境中考虑的。在真实的网络系统中，一台计算机必须由多个用户使用，执行多项任务。我们开发了一种在这样一个动态环境中工作的并行处理方法。较少

In order to give parallel processing technology for multimedia information within the framework of artificial intelligence (AI) systems, we have investigated elements for the technology. We also enhanced these elements which are explained as follows.1. Research on an intellectual drawing algorithm and a 'kansei' expression methodWe developed algorithms for AI systems to understand, to interpret and to express multimedia information. Then, we combined these algorithms with a recognition method and an inductive learning method, which are investigated separately. Thus, the combined algorithm achieves a high-level processing. We also inspected it in an artistic domain for 'kansei' expression.2. Research on music information processingWe developed a music composition and arrangement system based on a fractal technology, which has been used for image coding. Then, we enhanced this system in order to give total configuration of music. The enhanced system can generate and express not only main … More melodies but also counter parts of music and other parts of music, by considering structure of music.3. Research on problem solving methods using a strategic solution methodWe developed a method to induce, to generalize and to use strategic knowledge for the general problem solving framework. Its effect is inspected in an application area. We also investigated another approach within evolutionary methods. Combining these two approaches are remain for future works.4. Knowledge acquisition using parallel inductive learning algorithmsWe studied application of inductive learning methods to classify and to interpret multimedia information. We developed and compared three different approaches to parallelize the learning methods. This research archived a recognized result. We need to develop further enhancement to be used for larger scale applications.5. Research on a high-speed abductive reasoning method using a parallel techniquesIn the framework of abductive reasoning, we developed speed-up techniques using parallel processing. This is considered in a practical environment which consists of many computers connected by a network. In the real network system a computer must be used by many users and works for many tasks. We developed a parallel processing method that works in such a dynamic environment. Less