We applied Deep-Q Reinforcement Learning, with the use of CNNs, to manage a drone swarm scenario in a bi-dimensional environment. Given a square map with some targets, the goal is to make the drones able to learn to cooperate between them, trying to track and follow the most valuable targets. We compared a distributed and a centralized approach and verified how the first can outperform the latter in a real-world scenario with limited training.
Distributed Deep Reinforcement Learning for Drone Swarm Control
Venturini, Federico
2020/2021
Abstract
We applied Deep-Q Reinforcement Learning, with the use of CNNs, to manage a drone swarm scenario in a bi-dimensional environment. Given a square map with some targets, the goal is to make the drones able to learn to cooperate between them, trying to track and follow the most valuable targets. We compared a distributed and a centralized approach and verified how the first can outperform the latter in a real-world scenario with limited training.File in questo prodotto:
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Utilizza questo identificativo per citare o creare un link a questo documento:
https://hdl.handle.net/20.500.12608/22998