Editorial: Cognitive Informatics: Exploring the Theoretical Foundations for Natural Intelligence, Neural Informatics, Autonomic Computing, and Agent Systems Paper 1: toward Theoretical Foundations of Autonomic Computing
Editorial: Cognitive Informatics: Exploring the Theoretical Foundations for Natural Intelligence, Neural Informatics, Autonomic Computing, and Agent Systems Paper 1: toward Theoretical Foundations of Autonomic Computing
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Yingxu Wang
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作者：
Yingxu Wang
认知信息学（CI）研究大脑的自然智能和内部信息处理机制，以及感知和认知所涉及的过程。CI提供了一套连贯的基础理论和当代数学，构成了大多数信息和知识为基础的科学和工程学科，如计算机科学，认知科学，神经心理学，系统科学，控制论，计算机/软件工程和知识工程的基础。这篇社论解决了国际认知信息学和自然智能杂志（IJCINI）的目标，并探讨了CI领域及其跨学科性质。阐明了CI的历史演变及其理论基础。这一创刊号的覆盖面和CI的最新进展进行了审查。这篇社论表明，对CI的调查将导致对下一代信息和计算技术的发展的基本调查结果。摘要：自主计算（AC）是一种智能计算方法，它基于目标和推理驱动机制自主执行机器人和交互式应用程序。本文试图探讨AC的理论基础和技术范式。它回顾了导致从命令式计算过渡到AC的历史发展。它调查AC的跨学科理论基础，如行为主义，认知信息学，指称数学和智能科学。在此基础上，可以为跨学科的理论和应用范例建立一个面向AC的统一框架，这将导致新一代计算体系结构和新的信息处理系统的发展。
Cognitive informatics (CI) studies the natural intelligence and internal information processing mechanisms of the brain, as well as the processes involved in perception and cognition. CI provides a coherent set of fundamental theories, and contemporary mathematics, which form the foundation for most information and knowledge-based science and engineering disciplines such as computer science, cognitive science, neuropsychology, systems science, cybernetics, computer/software engineering, and knowledge engineering. This editorial addresses the objectives of the International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), and explores the domain of CI and its interdisciplinary nature. It clarifies the historical evolvement of CI and its theoretical foundations. The coverage of this inaugural issue and recent advances in CI are reviewed. This editorial demonstrates that the investigation into CI will result in fundamental findings towards the development of next generation information and computing technologies. Abstract: Autonomic computing (AC) is an intelligent computing approach that autonomously carries out robotic and interactive applications based on goal-and inference-driven mechanisms. This article attempts to explore the theoretical foundations and technical paradigms of AC. It reviews the historical development that leads to the transition from imperative computing to AC. It surveys transdisciplinary theoretical foundations for AC such as those of behaviorism, cognitive informatics, denotational mathematics, and intelligent science. On the basis of this work, a coherent framework toward AC may be established for both interdisciplinary theories and application paradigms, which will result in the development of new generation computing architectures and novel information processing systems.