عنوان
پدید آورنده
موضوع
رده
کتابخانه
محل استقرار
NATIONAL BIBLIOGRAPHY NUMBER
Number
TL54566
LANGUAGE OF THE ITEM
.Language of Text, Soundtrack etc
انگلیسی
TITLE AND STATEMENT OF RESPONSIBILITY
Title Proper
A Dynamic Territorializing Approach for Workload Balancing and Resource Management in a Distributed Multiagent System
General Material Designation
[Thesis]
First Statement of Responsibility
Islam, Mohammad Mahmudul
Subsequent Statement of Responsibility
Zargarzadeh, Hassan
.PUBLICATION, DISTRIBUTION, ETC
Name of Publisher, Distributor, etc.
Lamar University - Beaumont
Date of Publication, Distribution, etc.
2020
GENERAL NOTES
Text of Note
123 p.
DISSERTATION (THESIS) NOTE
Dissertation or thesis details and type of degree
D.E.
Body granting the degree
Lamar University - Beaumont
Text preceding or following the note
2020
SUMMARY OR ABSTRACT
Text of Note
In this work, a dynamic territorializing approach for the problem of distributing tasks among a group of robots, and a resource optimization algorithm for determining an appropriate number of agents for a distributed multiagent system has been proposed. Consider the scenario in which a task is comprised of two subtasks - detection and completion; two complementary teams of agents - hunters and gatherers, are assigned for the subtasks. Hunters are assigned with the task of exploring the environment, i.e., detection, whereas gatherers are assigned with the latter subtask. To minimize the workload among the gatherers, the proposed algorithm utilizes the center of mass of the known targets to form territories among the gatherers. The concept of center of mass has been adopted because it simplifies the task of territorial optimization and allows the system to dynamically adapt to changes in the environment by adjusting the assigned partitions as more targets are discovered. In addition, a game-theoretic analysis to justify the agents' reasoning mechanism to stay within their territory while completing the tasks has been presented. Moreover, simulation results are presented to analyze the performance of the proposed algorithm. First, an investigation on how the performance of the proposed algorithm varies as the frequency of territorializing is varied is conducted. Then, the effect of density of tasks on the performance of the algorithm is examined. Finally, the effectiveness of the proposed algorithm is verified by comparing its performance against an alternative approach. For resource optimization, where the hunters and gatherers are referred to as the resources, a more practical scenario is considered where some information about the environment is given a priori. The task assignment problem for the gatherers is modelled as a Travelling Salesman Problem (TSP) which in turn enables the development of the resource optimization algorithm. Statistical Analysis is conducted to illustrate the effectiveness of the proposed algorithm against several alternative approaches.
UNCONTROLLED SUBJECT TERMS
Subject Term
Artificial intelligence
Subject Term
Robotics
PERSONAL NAME - PRIMARY RESPONSIBILITY
Islam, Mohammad Mahmudul
PERSONAL NAME - SECONDARY RESPONSIBILITY
Zargarzadeh, Hassan
CORPORATE BODY NAME - SECONDARY RESPONSIBILITY
Lamar University - Beaumont
ELECTRONIC LOCATION AND ACCESS
Electronic name
مطالعه متن کتاب p
[Thesis]
276903
a
Y
