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Deutsch(DE) Schr\"odinger Bridges over Kinetic Swarming Models

Schrödinger Bridges method steers swarms toward target configurations

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new method for steering swarms of agents, such as those used in bio-inspired robotics or targeted therapy, towards specific configurations within a set time. This approach utilizes the theory of Schrödinger bridges, which involves finding an optimal control to correct a stochastic dynamic system. The method is applicable to mean-field models with Cucker--Smale alignment or Morse attraction--repulsion interactions, and can steer the swarm based on full phase-space distributions or just position marginals. Numerical examples demonstrate that the optimal control can either enhance or counteract the agents' inherent interaction forces to achieve the desired outcome. AI

IMPACT This research could lead to more precise control over collective behaviors in AI-driven systems, impacting areas like robotics and autonomous systems.

RANK_REASON This is a research paper detailing a new theoretical framework and numerical methods for controlling multi-agent systems. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Schrödinger Bridges method steers swarms toward target configurations

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This is a research paper detailing a new theoretical framework and numerical methods for controlling multi-agent systems. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv stat.ML TIER_1 Deutsch(DE) · Asmaa Eldesoukey, Md Zulfiqur Haider, Italo Napolitano, Yongxin Chen, Abhishek Halder ·

    Schr"odinger Bridges over Kinetic Swarming Models

    arXiv:2608.25281v1 Announce Type: cross Abstract: Paradigmatic interaction models explain how collective behaviors can emerge in complex systems from interactions among the constituent agents. In bio-inspired swarms, however, interactions alone may not suffice to bring the popula…

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