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Cognitive Informatics and Denotational Mathematical Means for Brain Informatics

机译:认知信息学和脑信息学的指称数学方法

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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:认知信息学通过一种理论和一种计算方法来研究自然智能和大脑,该方法通过称为抽象智能的基本理论来严格解释大脑的机制,并通过当代的指称数学对大脑进行正式建模。本文作为在AMT-BI 2010上发表的主题演讲的扩展摘要,描述了认知信息学,抽象智能,指称数学,脑信息学和计算智能之间的相互作用。阐述了认知信息学中发展的脑信息学的一些理论基础。在认知信息学的最新研究中认识到的一个关键概念是,自然,抽象和人工智能(尤其是认知信息学和脑信息学)的根本和深远目标是为满足他们的特殊需求寻找合适的数学方法。在过去的六十年中失踪了。为了探索脑信息学的理论框架,系统地开发了大脑的分层参考模型和思维的一系列认知过程。审查了目前的大脑研究方法,并分析了它们的优缺点。大脑信息学已经认识到认知信息学和指称数学的广泛应用,以实现高度智能的系统,例如全球智慧(WWW +),认知知识搜索引擎,自主学习机和认知机器人。

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