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Cognitive Informatics and Denotational Mathematical Means for Brain Informatics

机译:认知信息学与脑信息学的指示数学手段

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Cognitive informatics studies the natural intelligence and the brain from a theoretical and a computational approach, which rigorously explains the mechanisms of the brain by a fundamental theory known' as abstract intelligence, and formally models the brain by contemporary denotational mathematics. This paper, as an extended summary of the invited keynote presented in AMT-BI 2010, describes the interplay of cognitive informatics, abstract intelligence, denotational mathematics, brain informatics, and computational intelligence. Some of the theoretical foundations for brain informatics developed in cognitive informatics are elaborated. A key notion recognized in recent studies in cognitive informatics is that the root and profound objective in natural, abstract, and artificial intelligence in general, and in cognitive informatics and brain informatics in particular, is to seek suitable mathematical means for their special needs that were missing in the last six decades. A layered reference model of the brain and a set of cognitive processes of the mind are systematically developed towards the exploration of the theoretical framework of brain informatics. The current methodologies for brain studies are reviewed and their strengths and weaknesses are analyzed. A wide range of applications of cognitive informatics and denotational mathematics are recognized in brain informatics toward the implementation of highly intelligent systems such as world-wide wisdom (WWW+), cognitive knowledge search engines, autonomous learning machines, and cognitive robots.
机译:认知信息学研究了从理论和计算方法的自然智力和大脑研究,这严格地解释了大脑的基本理论被称为抽象智能的基本理论,并通过当代的指征数学正式模仿大脑。本文作为AMT-BI 2010中介绍的邀请的keynote的扩展摘要,描述了认知信息学,抽象智能,表示数学,脑信息学和计算智能的相互作用。阐述了认知信息学中开发的大脑信息学的一些理论基础。最近在认知信息学的研究中公认的一个关键概念是,特别是自然,摘要和人工智能的根本和深刻的目标,特别是在认知信息学和大脑信息学中,是为他们的特殊需求寻求合适的数学手段在过去的六十年中失踪了。系统地开发了大脑的分层参考模型和一组认知过程,以探索脑信息学的理论框架。综述了大脑研究的目前的方法,分析了它们的优点和缺点。在大脑信息学中,在大脑信息中识别出高度智能系统(如世界范围的智慧(www +),认知知识搜索引擎,自主学习机和认知机器人的高度智能系统的实施。

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