Biomimetic self-regulation in intrinsically motivated robots

Abstract

From weaving spiders to hibernating mammals and migratory birds, nature presents numerous examples of organisms exhibiting extraordinary autonomous behaviors that ensure their self-maintenance. However, physiological needs often interact and compete. This requires living organisms to handle them as a coordinated system of internal needs rather than as isolated subsystems. We present an artificial agent equipped with a neural mass model replicating fundamental self-regulatory behaviors observed in desert lizards. Our results demonstrate that this agent not only autonomously regulates its internal temperature by navigating to areas with optimal environmental conditions, but also harmonizes this process with other internal needs, such as energy, hydration, security, and mating. This biomimetic agent outperforms a control agent lacking interoceptive awareness in terms of efficiency, fairness, and stability. Additionally, to demonstrate the flexibility of our framework, we develop a "cautious" agent that prioritizes security over other needs, achieving a Maslow-like hierarchical organization of internal needs. Together, our findings suggest that grounding robot behavior in biological principles of self-regulation provides a robust framework for designing multipurpose, intrinsically motivated agents capable of resolving trade-offs in dynamic environments.