Control of Multi-Agent Swarms with Cooperative Particle Swarm Optimization

Abstract

This report describes a new approach for the distributed control of multi-agent systems that are performing search in uncertain environments. Thisapproach is called Cooperative Particle Swarm Optimization (Cooperative PSO), and is derived as a modification of Particle Swarm Optimization(PSO) that accounts for uncertainty in the search environment. This research develops a Cooperative PSO technique and illustrates how it can beapplied to physical search systems (such as robotic swarms) to successfully control the cooperative behavior of a small swarm of agents.Simulation experiments are performed to show the algorithms effectiveness via comparisons against conventional PSO in scenarios with uncertainsearch environments.

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Document Details

Document Type
Technical Report
Publication Date
Jun 06, 2019
Accession Number
AD1145299

Entities

People

  • Kyle D. Demedeiros
  • Thomas Wettergren

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Automata Theory
  • Autonomous Systems
  • Cognitive Systems Engineering
  • Computational Science
  • Control Systems
  • Cooperative Control
  • Data Mining
  • Evolutionary Algorithms
  • Information Systems
  • Motion Planning
  • Multiagent Systems
  • Particle Swarm Optimization
  • Simulations
  • Swarm Intelligence
  • Unmanned Underwater Vehicles

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Aerospace Engineering
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control