Fundamental concepts of cognitive mimetics

IF 2.1 3区 心理学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Cognitive Systems Research Pub Date : 2023-08-11 DOI:10.1016/j.cogsys.2023.101166
Antero Karvonen , Tuomo Kujala , Tommi Kärkkäinen , Pertti Saariluoma
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Abstract

The rapid development and widespread adoption of Artificial Intelligence (AI) technologies have made the development of AI-specific design methods an important topic to advance. In recent decades, the centre of gravity in AI has shifted away from cognitive science and related fields like psychology. However, there is a clear need and potential for added value in returning to stronger interaction. One potential challenge for this interaction may be the lack of common conceptual grounds and design languages.

In this article, we aim to contribute to the development of conceptual interfaces for human-based AI-specific design methods through the idea of cognitive mimetics. We begin by introducing basic concepts from mimetic design and interpret them in the context of this thematic area. These provide some of the basic building blocks for a design language and bring to the surface key questions. These in turn provide a ground for explicating cognitive mimetics. In the second part of this paper, we focus on specifying a key aspect in cognitive mimetics: the contents of information processes.

Others engaged in this field can derive value from using or developing the basic conceptual machinery to specify their own approaches in this interdisciplinary field that is still shaping itself. Furthermore, those who resonate with the idea of cognitive mimetics, as specified here, can join in taking this particular approach further.

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认知拟态学的基本概念
人工智能(AI)技术的快速发展和广泛采用,使得人工智能专用设计方法的发展成为一个重要的推进课题。近几十年来,人工智能的重心已经从认知科学和心理学等相关领域转移。然而,回归更强的相互作用显然有增加价值的需要和潜力。这种交互的一个潜在挑战可能是缺乏共同的概念基础和设计语言。在本文中,我们的目标是通过认知模拟的思想,为基于人类的人工智能特定设计方法的概念界面的发展做出贡献。我们首先介绍模仿设计的基本概念,并在这个主题区域的背景下解释它们。它们为设计语言提供了一些基本的构建块,并使关键问题浮出水面。这些反过来又为解释认知模仿提供了基础。在本文的第二部分中,我们着重说明了认知模拟的一个关键方面:信息处理的内容。从事这一领域的其他人可以从使用或发展基本概念机制中获得价值,以在这个仍在形成自身的跨学科领域中指定他们自己的方法。此外,那些与认知模仿学产生共鸣的人,如本文所述,可以加入到这一特殊方法的进一步发展中。
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来源期刊
Cognitive Systems Research
Cognitive Systems Research 工程技术-计算机:人工智能
CiteScore
9.40
自引率
5.10%
发文量
40
审稿时长
>12 weeks
期刊介绍: Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial. The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition. Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.
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