IMAP-QL: an improved multi-agent pursuit path-planning based on Q-learning Online publication date: Fri, 10-May-2024
by Mohammed El Habib Souidi; Makhlouf Ledmi; Toufik Messaoud Maarouk; Abdeldjalil Ledmi; Ferial Laassami
International Journal of Systems, Control and Communications (IJSCC), Vol. 15, No. 2, 2024
Abstract: Multi-agent path planning is a complex problem aiming to find the shortest trajectory. In this paper, we propose a cooperative path planning based on a hybridisation of two motion behaviours. The first behaviour concerns the strategy in which the agents are independently moving to their common objective according to the detected environment's rewards. The second behaviour is based on the leader-followers strategy through which the follower agents are moving in the direction of their leader agent to achieve their objectives. The goal of this work is to provide an equilibrium between these two approaches by allowing the follower agents to move in the direction of the objective instead of following the leader in some cases to decrease the execution time. To prove the approach's feasibility, we applied it to the multi-pursuer multi-evader game in comparison with the recent approaches. The obtained results prove the efficiency of the proposed approach.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Systems, Control and Communications (IJSCC):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook