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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM57448

Multi-Agent Reinforcement Learning for Autonomous Drone Swarm Navigation

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM57448

Volume:

10 |

3 |

Mar 2026

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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10.55041/IJSREM57448

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

M

Mrs.K.Jayasri1

P

P.Hemasree2

A

A.Subhash3andE.KavyaPrasanna4

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Abstract

Multi-Agent Reinforcement Learning (MARL) for Autonomous Drone Swarm Navigation is an intelligent system designed to enable multiple drones to coordinate and navigate efficiently in complex environments. The system uses reinforcement learning techniques where each drone acts as an independent agent that learns optimal navigation strategies through interaction with the environment. By continuously analyzing factors such as obstacle positions, distance to targets, energy consumption, and the positions of other drones in the swarm, the system determines the most efficient paths for navigation.

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Cite This Article

Mrs.K.Jayasri1, P.Hemasree2, A.Subhash3andE.KavyaPrasanna4, "Multi-Agent Reinforcement Learning for Autonomous Drone Swarm Navigation," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 3, Mar 2026. https://doi.org/10.55041/IJSREM57448

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11/2/2026

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Review Rounds: 2

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