Skip navigation
Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01ns0649150
Title: Decision Making and Task Allocation in a Multi-Robot System
Authors: Sadalgekar, Gargi
Wilson, Samarie
Walrath, Jacob
Advisors: Leonard, Naomi
Department: Mechanical and Aerospace Engineering
Certificate Program: Robotics & Intelligent Systems Program
Class Year: 2021
Abstract: We investigate several methods of explore-exploit decision making for the application of trash collection. To do this, we explore the optimization of the multi-agent Multi-Armed Bandit (MAMAB) problem using the UCB1 algorithm. We consider cases of inter-agent message passing and no message passing, as well as several re-ward distributions. We show that for fixed initial and constant rate addition reward distributions, performance improves as the degree of communication increases. We also show that beyond a certain degree of communication, there is negligible improvement in system performance. We develop a novel simulator for MAMAB problems to verify our theoretical results. We demonstrate that our adaptation of UCB1 achieves cumulative regret logarithmically with time, and is a valid approach to the trash collection problem.
URI: http://arks.princeton.edu/ark:/88435/dsp01ns0649150
Type of Material: Princeton University Senior Theses
Language: en
Appears in Collections:Mechanical and Aerospace Engineering, 1924-2021

Files in This Item:
File Description SizeFormat 
SADALGEKAR-GARGI-THESIS.pdf3.17 MBAdobe PDF    Request a copy


Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.