Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Multi-Agent Deep Reinforcement Learning for Hybrid Motion Planning in Dynamic Environments Subject The topic of the resource Autonomous agents; Distributed algorithms; Dynamic obstacles; Multi-agent systems; Trajectory optimization Description An account of the resource This research presents a novel approach to addressing the challenges of gesture forecasting in impenetrable and dynamic atmospheres by integrating a hybrid algorithm within a multi-agent system framework. Traditional methods such as Force-based motion planning (FMP) &amp; deep reinforcement learning (RL) often struggle to handle complex scenarios involving multiple autonomous agents due to their inherent limitations. To overcome these challenges, we propose a hybrid algorithm that seamlessly combines the strengths of RL and FMP while leveraging the coordination capabilities of a multi-agent system. By integrating this hybrid algorithm into a multi-agent framework, we demonstrate its effectiveness in enabling multiple agents to navigate densely populated environments with dynamic obstacles. Through extensive simulation studies, we illustrate the superior performance of our approach compared to traditional methods, achieving higher success rates and improved efficiency in scenarios involving simultaneous motion planning for multiple agents. A hybrid motion planning algorithm is also introduced in this very research. Performance Comparison of Hybrid Algorithm, Deep RL, and FMP are also discussed in the result section. This research paves the way for the development of robust and scalable solutions for motion planning in real-world applications such as collaborative robotics, autonomous vehicle fleets, and intelligent transportation systems. 2024 IEEE. Creator An entity primarily responsible for making the resource Chopra J.; Avhad P.; Ekatpure S.R.; Rallapalli M.; Kumari S.; Upreti K. Source A related resource from which the described resource is derived 2024 International Conference on Emerging Trends in Networks and Computer Communications, ETNCC 2024 - Proceedings, pp. 235-241. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ETNCC63262.2024.10767440" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ETNCC63262.2024.10767440</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214684879&amp;doi=10.1109%2FETNCC63262.2024.10767440&amp;partnerID=40&amp;md5=1e10434ba46d93093427e9f32ac6bfc0" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214684879&amp;doi=10.1109%2fETNCC63262.2024.10767440&amp;partnerID=40&amp;md5=1e10434ba46d93093427e9f32ac6bfc0</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835035326-6 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Chopra J., SEAS, GWU, Washington, DC, United States; Avhad P., Computer Engineering, Veermata Jijabai Technological Inst., Mumbai, India; Ekatpure S.R., Industrial Engineering, Kulicke and Soffa, PA, United States; Rallapalli M., CSE - AI, JAIN University, Bengaluru, India; Kumari S., HSBC, Maharashtra, India; Upreti K., Computer Science Engineering, CHRIST University, Delhi Ncr, India