Robodiment, Self and Temporality:Phenomenological Insights for Cognitive Architectures in Robotics

Abstract Cognitive architectures are simplified models of complex neural and behavioral processes, designed to equip artificial agents with flexibility and adaptive behavior. To enhance context-awareness and autonomy in humanoid robots, it is essential to address the role of temporality. The temporal dimension extends far beyond its association with memory, encompassing the continuity of self and identity over time, along with cognitive processes such as intention formation and action planning. This article focuses on the concept of intrinsic temporality as a prereflective structural feature underlying human perceptual experience and motor system activity.Drawing on Husserl’s retentional-protentional dynamic, as interpreted in phenomenology and applied in predictive processing approaches, this article suggests that intrinsic temporality underlying prereflective self-monitoring can be adapted to enrich the design of a cognitive architecture for humanoid robots.