From Smart Sensing to consciousness: An info-structural model of computational consciousness for non-interacting agents

IF 2.1 3区 心理学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Cognitive Systems Research Pub Date : 2023-09-01 DOI:10.1016/j.cogsys.2023.05.003
Gerardo Iovane , Riccardo Emanuele Landi
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Abstract

This study proposes a model of computational consciousness for non-interacting agents. The phenomenon of interest was assumed as sequentially dependent on the cognitive tasks of sensation, perception, emotion, affection, attention, awareness, and consciousness. Starting from the Smart Sensing prodromal study, the cognitive layers associated with the processes of attention, awareness, and consciousness were formally defined and tested together with the other processes concerning sensation, perception, emotion, and affection. The output of the model consists of an index that synthesizes the energetic and entropic contributions of consciousness from a computationally moral perspective. Attention was modeled through a bottom-up approach, while awareness and consciousness by distinguishing environment from subjective cognitive processes. By testing the solution on visual stimuli eliciting the emotions of happiness, anger, fear, surprise, contempt, sadness, disgust, and the neutral state, it was found that the proposed model is concordant with the scientific evidence concerning covert attention. Comparable results were also obtained regarding studies investigating awareness as a consequence of visual stimuli repetition, as well as those investigating moral judgments to visual stimuli eliciting disgust and sadness. The solution represents a novel approach for defining computational consciousness through artificial emotional activity and morality.

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从智能感知到意识:非交互主体计算意识的信息结构模型
本研究提出了一个非交互主体的计算意识模型。兴趣现象被假定为依次依赖于感觉、感知、情绪、情感、注意力、意识和意识等认知任务。从智能感知前驱研究开始,与注意力、意识和意识过程相关的认知层被正式定义,并与其他有关感觉、感知、情绪和情感的过程一起进行测试。该模型的输出由一个指数组成,该指数从计算道德的角度综合了意识的能量和熵贡献。注意力是通过自下而上的方法建模的,而意识和意识是通过区分环境和主观认知过程来建模的。通过对引发快乐、愤怒、恐惧、惊讶、蔑视、悲伤、厌恶和中性状态情绪的视觉刺激的解决方案进行测试,发现所提出的模型与关于隐性注意力的科学证据一致。调查视觉刺激重复引起的意识的研究,以及调查对引起厌恶和悲伤的视觉刺激的道德判断的研究,也获得了可比较的结果。该解决方案代表了一种通过人工情感活动和道德来定义计算意识的新方法。
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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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