Reinforcement learning algorithms: A brief survey
Reinforcement Learning (RL) is a machine learning (ML) technique to learn sequential
decision-making in complex problems. RL is inspired by trial-and-error based human/animal …
decision-making in complex problems. RL is inspired by trial-and-error based human/animal …
Deep reinforcement learning in production systems: a systematic literature review
Shortening product development cycles and fully customisable products pose major
challenges for production systems. These not only have to cope with an increased product …
challenges for production systems. These not only have to cope with an increased product …
Review and evaluation of reinforcement learning frameworks on smart grid applications
With the rise in electricity, gas and oil prices and the persistently high levels of carbon
emissions, there is an increasing demand for effective energy management in energy …
emissions, there is an increasing demand for effective energy management in energy …
[HTML][HTML] Reinforcement learning for swarm robotics: An overview of applications, algorithms and simulators
MA Blais, MA Akhloufi - Cognitive Robotics, 2023 - Elsevier
Robots such as drones, ground rovers, underwater vehicles and industrial robots have
increased in popularity in recent years. Many sectors have benefited from this by increasing …
increased in popularity in recent years. Many sectors have benefited from this by increasing …
Reinforcement learning in game industry—review, prospects and challenges
K Souchleris, GK Sidiropoulos, GA Papakostas - Applied Sciences, 2023 - mdpi.com
This article focuses on the recent advances in the field of reinforcement learning (RL) as well
as the present state–of–the–art applications in games. First, we give a general panorama of …
as the present state–of–the–art applications in games. First, we give a general panorama of …
Single-image reflection removal using deep learning: a systematic review
Images captured through the glass often consist of undesirable specular reflections. These
reflections detected in front of the glass remarkably reduce the quality and visibility of the …
reflections detected in front of the glass remarkably reduce the quality and visibility of the …
Optimized Inverse Kinematics Modeling and Joint Angle Prediction for Six-Degree-of-Freedom Anthropomorphic Robots with Explainable AI
Inverse kinematics, crucial in robotics, involves computing joint configurations to achieve
specific end-effector positions and orientations. This task is particularly complex for six …
specific end-effector positions and orientations. This task is particularly complex for six …
Reinforcement learning in construction engineering and management: A review
The construction engineering and management (CEM) domain frequently meets complex
tasks due to the unavoidable complicated operation environments and the involvement of …
tasks due to the unavoidable complicated operation environments and the involvement of …
Industry 5 and the human in Human-Centric manufacturing
K Briken, J Moore, D Scholarios, E Rose, A Sherlock - Sensors, 2023 - mdpi.com
Industry 4 (I4) was a revolutionary new stage for technological progress in manufacturing
which promised a new level of interconnectedness between a diverse range of …
which promised a new level of interconnectedness between a diverse range of …
Affordance-based human–robot interaction with reinforcement learning
F Munguia-Galeano, S Veeramani… - IEEE …, 2023 - ieeexplore.ieee.org
Planning precise manipulation in robotics to perform grasp and release-related operations,
while interacting with humans is a challenging problem. Reinforcement learning (RL) has …
while interacting with humans is a challenging problem. Reinforcement learning (RL) has …