Classifying Emergence in Robot Swarms: An Observer-Dependent Approach

2025-07-09

AI Summary

The concepts of “swarm” and “emergence” in robotic swarms lack conceptual consensus, hindering rigorous design, evaluation, and interdisciplinary discourse. Method: We propose an observer-centered theoretical framework that distinguishes external observable states from internal latent states, formally defining swarm and emergence as observer-dependent phenomena—contingent on the observer’s cognitive background, perceptual perspective, and observational scale—rather than intrinsic system properties. Crucially, we argue that swarmhood resides in behavior-generation mechanisms, not superficial characteristics, and that the key distinction between multi-robot systems and true swarms lies in the presence of observer-dependent emergent behavior. Contribution/Results: Through conceptual modeling and formal analysis, we establish a unifying theoretical framework that clarifies conceptual boundaries, enables systematic comparison across existing definitions, and provides foundational conceptual tools for swarm system design, empirical assessment, and cross-disciplinary communication.

Technology Category

• Intelligent Robots: Multi-Robot Systems
• Multiagent Systems: Agent-Based Simulation and Emergent Behavior
• Cognitive Modeling & Cognitive Systems: Conceptual Inference and Reasoning

Application Category

• Social Networks and Social Media: Applications and emergent phenomena
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Emergence and swarms are widely discussed topics, yet no consensus exists on their formal definitions. This lack of agreement makes it difficult not only for new researchers to grasp these concepts, but also for experts who may use the same terms to mean different things. Many attempts have been made to objectively define 'swarm' or 'emergence,' with recent work highlighting the role of the external observer. Still, several researchers argue that once an observer's vantage point (e.g., scope, resolution, context) is established, the terms can be made objective or measured quantitatively. In this note, we propose a framework to discuss these ideas rigorously by separating externally observable states from latent, unobservable ones. This allows us to compare and contrast existing definitions of swarms and emergence on common ground. We argue that these concepts are ultimately subjective-shaped less by the system itself than by the perception and tacit knowledge of the observer. Specifically, we suggest that a 'swarm' is not defined by its group behavior alone, but by the process generating that behavior. Our broader goal is to support the design and deployment of robotic swarm systems, highlighting the critical distinction between multi-robot systems and true swarms.

Problem

• Defining 'swarm' and 'emergence' objectively is challenging
• Observer's perspective shapes swarm and emergence definitions
• Framework separates observable and latent states for clarity

Innovation

• Observer-dependent framework for swarm classification
• Separates observable and latent states rigorously
• Defines swarm by behavior-generating process