ISEED: an always-on cognitive architecture for experience-driven interaction-oriented humanoid robots

Abstract

Current cognitive architectures for social robots, even when conceived as autonomous and adaptable, remain largely grounded in fully digital, von Neumann–style paradigms, where acquired knowledge is detached from individual experience. This contrasts with biological cognition, in which learning emerges from continuous, embodied interaction which leads to personal, non-copyable competencies. In this perspective, we argue that achieving truly adaptive and socially situated robotic agents requires a paradigm shift toward hybrid, bio-inspired, always-on architectures, where dynamic, and digitally implementable components coexist. Such architecture supports continuous activity, structural plasticity, and experience-dependent learning, enabling knowledge to emerge and strengthen from distributed interactions rather than from copiable parameters. We outline a roadmap in which embodiment, dynamical systems, endogenous values, and socially grounded learning mechanisms are central design principles of such cognitive architecture, and we discuss how these ideas can scale beyond sensorimotor skills toward what we believe being important for social robots. These principles are currently being explored in a bioinspired initiative (iCog) aimed at developing the ISEED (Interaction-oriented Situated Embodied Experience-Driven) cognitive architecture, a framework for humanoid social robots, meant to be a testbed for implementing and validating a hybrid, experience-driven approach for real-world cooperative robot partners.