Modeling and Mathematical Analysis of Swarms of Microscopic Robots
Aram Galstyan, Tad Hogg, Kristina Lerman
Abstract
The biologically-inspired swarm paradigm is being used to design self-organizing systems of locally interacting artificial agents. A major difficulty in designing swarms with desired characteristics is understanding the causal relation between individual agent and collective behaviors. Mathematical analysis of swarm dynamics can address this difficulty to gain insight into system design. This paper proposes a framework for mathematical modeling of swarms of microscopic robots that may one day be useful in medical applications. While such devices do not yet exist, the modeling approach can be helpful in identifying various design trade-offs for the robots and be a useful guide for their eventual fabrication. Specifically, we examine microscopic robots that reside in a fluid, for example, a bloodstream, and are able to detect and respond to different chemicals. We present the general mathematical model of a scenario in which robots locate a chemical source. We solve the scenario in one-dimension and show how results can be used to evaluate certain design decisions.
Create a lesson
Related papers
Beyond Division of Labor: How Roles Shape Feedback and Recovery in Multi-Agent Systems
Chih-Hsuan Yang, Xinyang Li, Rajeev Thakur et al.
Cloudra: Geometric Reasoning and Scientific Validation for Autonomous Reaction Mechanism Exploration
Chengyi Yang, Qianxin Zhou, Yang Li
AGiR: Mitigating Gift Over-Reliance in Mixed-Motive Games
Woohyeon Byeon, Seongmin Kim, Jiwon Jeon et al.
Multi-Modal Multi-Agent System for Bridge Operation and Maintenance based on Large Language Model
Xiangyun Luo, Yunkai Zhang, Yong Huang et al.
Coati: Host-Grounded Execution for Installable Mobile GUI Agents
Yudou Ying, Pu Shi, Hanlei Shi et al.
Organizational Learning in Materials Discovery Campaigns: Which Databases, Calculations, and Agent Teams Pay Off
Kinston Ackölf, Taylor D. Sparks