EFFICIENT AND FAIR DECENTRALIZED TASK ALLOCATION ALGORITHMS FOR AUTONOMOUS VEHICLES

Abstract

The proposed project aims at improving the efficiency of the multi-agent decentralized allocation with considerations in computation, communication, strategic, fairness and adaptability for real-life applications. Auction-based method such as the Consensus-based auction algorithm (CBAA) are effective methods for decentralized task assignment with bounded optimality and guaranteed convergence. The methods have very few theoretical guarantees in terms of approximation of the global objectives such as maximizing welfare or minimizing costs. The goals of the project include extending existing approaches to cater for more general feasibility constraints and achieving desirable approximation guarantees.

Document Details

Document Type
DoD Grant Award
Publication Date
Aug 11, 2021
Source ID
FA23862014063

Entities

People

  • Haris Aziz

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • University of New South Wales

Tags

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Mathematical Modeling and Probability Theory.

Technology Areas

  • Autonomy
  • Autonomy - Autonomous System Control