Robots that behave like animals by adapting continuously to changes

Beyond Tasks: A Vision for Reproducing an Animal-like Behavioral Substrate Using Modern Robot Learning Techniques

RoboticsArtificial IntelligenceHuman-Computer Interaction

Summary

Most robot learning focuses on teaching machines specific skills or tasks, but animals do something different—they keep behaving in a sensible and flexible way as their surroundings and goals change. The authors suggest thinking of this ongoing flexible behavior as a kind of foundation, or 'behavioral substrate,' for robots. They propose studying robots that act as animal companions to people over long periods to better understand how continuous adaptation, memory, and social behavior can emerge in machines. This approach may help robots develop ongoing, sensible behaviors alongside more advanced abilities.

What this means in practice

  • For robotics teams: Create robot animal companions capable of sustained social interaction and adaptation in changing human environments.
  • For game developers: Design game characters or NPCs that show ongoing adaptive behavior rather than fixed isolated skills.

A position paper. It proposes an approach and reports no results.

Authors

Samiyuru Menik, Hemadri Jayalath

Abstract

Recent advances in robot learning have produced increasingly capable embodied agents. Yet comparatively less attention has been given to a more basic form of competence that animals exhibit continuously: the ability to remain situated, responsive, and behaviorally coherent as physical, environmental, and social demands change over time. We propose the ethological behavioral substrate as a conceptual lens for studying this form of competence in artificial agents. Rather than treating these behaviors that animals exhibit as a set of isolated skills, we argue that their continual coordination under competing demands constitutes an important and underexplored target for modern robot learning. We further propose robotic animal companions as a useful research setting for studying sustained interaction and adaptation in human-centered environments. Such systems provide an opportunity to investigate how social behavior, memory, and continual learning develop over long periods of interaction. This perspective motivates further investigation of how such persistent behavioral competence may complement higher-level capabilities in embodied agents.
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