Structural transition in the collective behavior of cognitive agents

Area of Science:

• Computational neuroscience
• Swarm intelligence
• Cognitive science

Background:

• Organisms process environmental information for survival and adaptation.
• Collective behavior and optimization strategies are common in nature.
• Environmental structure shapes internal architectures and adaptive responses.

Purpose of the Study:

• To model agents exploring environments using sampling trajectories.
• To define cognitive maps based on spatial information from trajectories.
• To investigate pattern emergence and information exchange in cognitive agents.

Main Methods:

• Development of a minimal agent-based model.
• Simulation of agents exploring environments and building cognitive maps.
• Analysis of pattern formation related to cognitive map overlap.
• Investigation of information exchange effects on system order.

Main Results:

• Complex patterns emerge as agents update cognitive maps.
• Pattern formation correlates with the spatial overlap of cognitive maps.
• Information exchange induces an order-disorder transition.
• A Goldstone mode emerges, indicating collective information transfer.

Conclusions:

• Cognitive map formation and overlap drive emergent collective behavior.
• Information exchange facilitates a transition to ordered states.
• Findings suggest potential applications for decentralized artificial intelligence swarm systems.