Rudrauf David, Sergeant-Perthuis Grégoire, Tisserand Yvain, Poloudenny Germain, Williford Kenneth, Amorim Michel-Ange
CIAMS, Université Paris-Saclay, 91405 Orsay, France.
CIAMS, Université d'Orléans, 45067 Orléans, France.
Brain Sci. 2023 Oct 9;13(10):1435. doi: 10.3390/brainsci13101435.
Consciousness has been described as acting as a global workspace that integrates perception, imagination, emotion and action programming for adaptive decision making. The mechanisms of this workspace and their relationships to the phenomenology of consciousness need to be further specified. Much research in this area has focused on the neural correlates of consciousness, but, arguably, computational modeling can better be used toward this aim. According to the Projective Consciousness Model (PCM), consciousness is structured as a viewpoint-organized, internal space, relying on 3D projective geometry and governed by the action of the Projective Group as part of a process of active inference. The geometry induces a group-structured subjective perspective on an encoded world model, enabling adaptive perspective taking in agents. Here, we review and discuss the PCM. We emphasize the role of projective mechanisms in perception and the appraisal of affective and epistemic values as tied to the motivation of action, under an optimization process of Free Energy minimization, or more generally stochastic optimal control. We discuss how these mechanisms enable us to model and simulate group-structured drives in the context of social cognition and to understand the mechanisms underpinning empathy, emotion expression and regulation, and approach-avoidance behaviors. We review previous results, drawing on applications in robotics and virtual humans. We briefly discuss future axes of research relating to applications of the model to simulation- and model-based behavioral science, geometrically structured artificial neural networks, the relevance of the approach for explainable AI and human-machine interactions, and the study of the neural correlates of consciousness.
意识被描述为一个全局工作空间,它整合感知、想象、情感和行动规划以进行适应性决策。这个工作空间的机制及其与意识现象学的关系需要进一步明确。该领域的许多研究都集中在意识的神经关联上,但可以说,计算建模能更好地用于这一目的。根据投射意识模型(PCM),意识被构建为一个由视点组织的内部空间,依赖于三维投射几何,并受投射群的作用支配,作为主动推理过程的一部分。这种几何结构在编码的世界模型上诱导出一种群结构的主观视角,使智能体能够进行适应性的视角采择。在这里,我们回顾并讨论PCM。我们强调投射机制在感知以及情感和认知价值评估中的作用,这些评估与行动动机相关联,处于自由能最小化的优化过程中,或者更一般地说,处于随机最优控制之下。我们讨论这些机制如何使我们能够在社会认知的背景下对群结构驱动进行建模和模拟,并理解支撑共情、情感表达与调节以及趋近-回避行为的机制。我们回顾以前的结果,借鉴在机器人技术和虚拟人类中的应用。我们简要讨论与该模型在基于模拟和模型的行为科学中的应用、几何结构的人工神经网络、该方法与可解释人工智能和人机交互的相关性以及意识的神经关联研究相关的未来研究方向。