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.

翻译：本研究提出了一种面向非交互智能体的计算意识模型。研究对象被假设为依次依赖于感觉、知觉、情绪、情感、注意、觉知和意识等认知任务。从智能感知前期研究出发，本研究正式定义了与注意、觉知和意识过程相关的认知层，并与涉及感觉、知觉、情绪和情感的其他过程一同进行了测试。模型的输出由一项指数构成，该指数从计算道德的角度综合了意识的能量和熵贡献。注意通过自底向上的方法建模，而觉知和意识则通过区分环境与主观认知过程进行建模。通过在引发快乐、愤怒、恐惧、惊讶、轻蔑、悲伤、厌恶和中性状态等情绪的可视刺激上测试该方案，发现所提模型与关于隐性注意的科学证据一致。在关于意识作为可视刺激重复结果的研究，以及关于引发厌恶和悲伤的可视刺激的道德判断研究中也获得了可比结果。该方案通过人工情绪活动与道德定义计算意识，代表了一种新颖方法。