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Reinforcement Learning

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Autonomous Unmanned Aerial Vehicle Navigation Using Reinforcement Learning: A Systematic Review, Fadi Almahamid, Katarina Grolinger Aug 2022

Autonomous Unmanned Aerial Vehicle Navigation Using Reinforcement Learning: A Systematic Review, Fadi Almahamid, Katarina Grolinger

Electrical and Computer Engineering Publications

There is an increasing demand for using Unmanned Aerial Vehicle (UAV), known as drones, in different applications such as packages delivery, traffic monitoring, search and rescue operations, and military combat engagements. In all of these applications, the UAV is used to navigate the environment autonomously --- without human interaction, perform specific tasks and avoid obstacles. Autonomous UAV navigation is commonly accomplished using Reinforcement Learning (RL), where agents act as experts in a domain to navigate the environment while avoiding obstacles. Understanding the navigation environment and algorithmic limitations plays an essential role in choosing the appropriate RL algorithm to solve the …


Reinforcement Learning Algorithms: An Overview And Classification, Fadi Almahamid, Katarina Grolinger Sep 2021

Reinforcement Learning Algorithms: An Overview And Classification, Fadi Almahamid, Katarina Grolinger

Electrical and Computer Engineering Publications

The desire to make applications and machines more intelligent and the aspiration to enable their operation without human interaction have been driving innovations in neural networks, deep learning, and other machine learning techniques. Although reinforcement learning has been primarily used in video games, recent advancements and the development of diverse and powerful reinforcement algorithms have enabled the reinforcement learning community to move from playing video games to solving complex real-life problems in autonomous systems such as self-driving cars, delivery drones, and automated robotics. Understanding the environment of an application and the algorithms’ limitations plays a vital role in selecting the …