Cognitive Computing (COC) aims to build highly cognitive machines with low computational resources that respond in real-time. However, scholarly literature shows varying research areas and various interpretations of COC. This calls for a cohesive architecture that delineates the nature of COC. We argue that if Herbert Simon considered the design science is the science of artificial, cognitive systems are the products of cognitive science or 'the newest science of the artificial'. Therefore, building a conceptual basis for COC is an essential step into prospective cognitive computing-based systems. This paper proposes an architecture of COC through analyzing the literature on COC using a myriad of statistical analysis methods. Then, we compare the statistical analysis results with previous qualitative analysis results to confirm our findings. The study also comprehensively surveys the recent research on COC to identify the state of the art and connect the advances in varied research disciplines in COC. The study found that there are three underlaying computing paradigms, Von-Neuman, Neuromorphic Engineering and Quantum Computing, that comprehensively complement the structure of cognitive computation. The research discuss possible applications and open research directions under the COC umbrella.
翻译:认知计算(COC)旨在建设高度认知的机器,其计算资源低,能够实时作出反应。然而,学术文献显示不同的研究领域和对COC的不同解释。这要求建立一个具有凝聚力的结构,描述COC的性质。我们争辩说,如果赫伯特·西蒙认为设计科学是人工科学,认知系统是认知科学或“人工最新科学”的产物。因此,为COC建立概念基础是未来认知计算系统的一个必要步骤。本文通过使用多种统计分析方法分析COC的文献,提出了COC的架构。然后,我们将统计分析结果与先前的质量分析结果进行比较,以证实我们的调查结果。这项研究还全面调查了最近关于COC的研究,以确定艺术状况,并将COC不同研究学科的进展联系起来。研究发现,有三种内在的计算模式,即Von-Neuman、Neurormophic工程和Quntum计算,全面补充了认知计算结构。研究讨论了在COC伞下可能的应用和公开研究方向。