Trust Method for Multi-Agent Consensus

Abstract

The consensus problem in multi-agent systems often assumes that all agents are equally trustworthy to seek agreement. But for multi-agent military applications - particularly those that deal with sensor fusion or multi-robot formation control - this assumption may create the potential for compromised network security or poor cooperative performance. As such, we present a trust-based solution for the discrete-time multi-agent consensus problem and prove its asymptotic convergence in strongly connected digraphs. The novelty of the paper is a new trust algorithm called RoboTrust, which is used to calculate trustworthiness in agents using observations and statistical inferences from various historical perspectives. The performance of RoboTrust is evaluated within the trust-based consensus protocol under different conditions of tolerance and confirmation.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 22, 2012
Accession Number
ADA558994

Entities

People

  • Dariusz Mikulski
  • Edward Y. Gu
  • Frank L. Lewis
  • Greg R. Hudas

Organizations

  • University of Texas at Arlington

Tags

Communities of Interest

  • Autonomy
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Agreements
  • Algorithms
  • Consensus Algorithms
  • Convergence
  • Eigenvalues
  • Environment
  • Equations
  • Military Operations
  • Multiagent Systems
  • Observation
  • Probability
  • Probability Distributions
  • Random Variables
  • Robotics
  • Robots
  • Sensor Fusion
  • Simulations

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control
  • Autonomy - Human-Robot Interaction
  • Cyber
  • Cyber - Cryptography