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Language Evolution in Swarm Robotics: A Perspective.

Nicolas Cambier¹, Roman Miletitch², Vincent Frémont³

¹School of Computing, University of Leeds, Leeds, United Kingdom.

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|January 27, 2021

Summary

This summary is machine-generated.

This study proposes using language games to develop complex, adaptive communication in robot swarms. This approach moves beyond simple signaling, enabling more autonomous and versatile collective behaviors in artificial agents.

Keywords:

communication cultural evolution language evolution language games self-organization swarm robotics

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Area of Science:

Robotics
Artificial Intelligence
Computational Linguistics

Background:

Direct local communication in robot swarms is limited to simple tasks.
Current methods focus on offline evolution, yielding task-specific signals, not complex language.

Purpose of the Study:

To explore emergent communication in robot swarms using language games.
To enable more complex, adaptive, and autonomous collective behaviors in robot swarms.

Main Methods:

Advocating a language game-based approach for emergent communication.
Leveraging cultural self-organization principles observed in natural language development.

Main Results:

Language games can foster complexity and expressiveness in communication systems.
Robot swarms can serve as a test-bed for advancing language-like communication.

Conclusions:

Language games offer a path to sophisticated emergent communication in robot swarms.
This approach enhances swarm autonomy, adaptivity, and collective behavior complexity.