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

Summary

Human experience of self and time is not just about memory; it is a continuous, prereflective structure that underpins perception, intention, and action. Drawing on Husserl's phenomenology and predictive processing, this article argues that this intrinsic temporality—the retentional-protentional dynamic—can be adapted to improve cognitive architectures for humanoid robots. By modeling this temporal continuity, robots could gain greater context-awareness and autonomy, moving beyond simple memory to a more fluid sense of self and identity over time.

Study at a glance

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.