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。假定所关注的现象依次依赖于感知、知觉、情感、情绪、注意、觉察和意识等认知任务。以智能感知前驱研究为起点，本研究正式定义了与注意、觉察和意识过程相关的认知层，并与其他涉及感知、知觉、情感和情绪的过程一同进行了测试。模型输出一个指数，该指数从计算道德视角综合了意识的能量和熵贡献。注意采用自下而上的方法建模，而觉察和意识则通过区分环境与主观认知过程进行建模。通过对引发快乐、愤怒、恐惧、惊讶、轻蔑、悲伤、厌恶及中性状态等情绪的视觉刺激进行测试，发现所提出的模型与关于隐性注意的科学证据一致。在探究视觉刺激重复对觉察影响的研究，以及探究引发厌恶和悲伤的视觉刺激对道德判断影响的研究中，也获得了可比结果。该方案代表了通过人工情感活动与道德性定义计算意识的一种新颖方法。