A systematic study on reinforcement learning based applications
K Sivamayil, E Rajasekar, B Aljafari, S Nikolovski… - Energies, 2023 - mdpi.com
We have analyzed 127 publications for this review paper, which discuss applications of
Reinforcement Learning (RL) in marketing, robotics, gaming, automated cars, natural …
Reinforcement Learning (RL) in marketing, robotics, gaming, automated cars, natural …
[PDF][PDF] Applications of machine learning in aircraft maintenance
Aircraft maintenance is an expansive multidisciplinary field which entails robust design and
optimization of extensive maintenance operations and procedures; encompassing the fault …
optimization of extensive maintenance operations and procedures; encompassing the fault …
Autonomous UAV navigation with adaptive control based on deep reinforcement learning
Y Yin, Z Wang, L Zheng, Q Su, Y Guo - Electronics, 2024 - mdpi.com
Unmanned aerial vehicle (UAV) navigation plays a crucial role in its ability to perform
autonomous missions in complex environments. Most of the existing reinforcement learning …
autonomous missions in complex environments. Most of the existing reinforcement learning …
Accmer: Accelerating multi-agent experience replay with cache locality-aware prioritization
Multi-Agent Experience Replay (MER) is a key component of off-policy reinforcement
learning (RL) algorithms. By remembering and reusing experiences from the past …
learning (RL) algorithms. By remembering and reusing experiences from the past …
[HTML][HTML] An Integrated Geometric Obstacle Avoidance and Genetic Algorithm TSP Model for UAV Path Planning
In this paper, we propose an innovative approach for the path planning of Uninhabited
Aerial Vehicles (UAVs) that combines an advanced Genetic Algorithm (GA) for optimising …
Aerial Vehicles (UAVs) that combines an advanced Genetic Algorithm (GA) for optimising …
Explainable AI and counterfactuals for test and evaluation of intelligent engineered systems
Abstract Systems Engineering (SE) based test and evaluation (T&E) approaches have
proven crucial for successful realization of most modern‐day complex systems and system …
proven crucial for successful realization of most modern‐day complex systems and system …
Action Robust Reinforcement Learning for Air Mobility Deconfliction Against Conflict Induced Spoofing
Increased dynamic drone usage has increased complexity in aerial navigation and often
demands distributed local deconfliction. Due to the high velocities and few landmarks …
demands distributed local deconfliction. Due to the high velocities and few landmarks …
Exploring the role of simulator fidelity in the safety validation of learning‐enabled autonomous systems
A Baheri - AI Magazine, 2023 - Wiley Online Library
This article presents key insights from the New Faculty Highlights talk given at AAAI 2023,
focusing on the crucial role of fidelity simulators in the safety evaluation of learning‐enabled …
focusing on the crucial role of fidelity simulators in the safety evaluation of learning‐enabled …
[HTML][HTML] Optimization strategies for atari game environments: integrating snake optimization algorithm and energy valley optimization in reinforcement learning models
SMK Sarkhi, H Koyuncu - AI, 2024 - mdpi.com
One of the biggest problems in gaming AI is related to how we can optimize and adapt a
deep reinforcement learning (DRL) model, especially when it is running inside complex …
deep reinforcement learning (DRL) model, especially when it is running inside complex …
Integrated conflict management for uam with strategic demand capacity balancing and learning-based tactical deconfliction
Urban air mobility (UAM) has the potential to revolutionize our daily transportation, offering
rapid and efficient deliveries of passengers and cargo between dedicated locations within …
rapid and efficient deliveries of passengers and cargo between dedicated locations within …