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Gleice Kelly Barbosa Souza, Samara Oliveira Silva Santos, André Luiz Carvalho Ottoni, Marcos Santos Oliveira, Daniela Carine Ramires Oliveira and Erivelton Geraldo Nepomuceno
Reinforcement learning is an important technique in various fields, particularly in automated machine learning for reinforcement learning (AutoRL). The integration of transfer learning (TL) with AutoRL in combinatorial optimization is an area that requir...
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Hamed Taherdoost and Mitra Madanchian
In recent years, artificial intelligence (AI) has seen remarkable advancements, stretching the limits of what is possible and opening up new frontiers. This comparative review investigates the evolving landscape of AI advancements, providing a thorough e...
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Hao Sun, Zile Jia, Meng Zhao, Jiayuan Tian, Dan Liu and Yifei Wang
The current lack of a high-precision, real-time model applicable to the control optimization process of heat exchange systems, especially the difficulty in determining the overall heat transfer coefficient K of heat exchanger operating parameters in real...
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Rafet Durgut, Mehmet Emin Aydin and Abdur Rakib
In the past two decades, metaheuristic optimisation algorithms (MOAs) have been increasingly popular, particularly in logistic, science, and engineering problems. The fundamental characteristics of such algorithms are that they are dependent on a paramet...
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Ji-Hyeon Yoo, Ho-Jin Jung, Jang-Hyeon Kim, Dae-Han Sim and Han-Ul Yoon
Geduldspiele cubes (also known as patience cubes in English) are interesting problems to solve with robotic systems on the basis of machine learning approaches. Generally, highly dexterous hand and finger movement is required to solve them. In this paper...
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Rytis Maskeliunas, Robertas Damasevicius, Andrius Paulauskas, Maria Gabriella Ceravolo, Marina Charalambous, Maria Kambanaros, Eliada Pampoulou, Francesco Barbabella, Arianna Poli and Carlos V. Carvalho
This paper describes a serious game based on a knowledge transfer model using deep reinforcement learning, with an aim to improve the caretakers? knowledge and abilities in post-stroke care. The iTrain game was designed to improve caregiver knowledge and...
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Chang-Bae Gil and Jee-Hyong Lee
Manufacturing sites encounter various scheduling problems, which must be dealt with to efficiently manufacture products and reduce costs. With the development of smart factory technology, many elements at manufacturing sites have become unmanned and more...
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Zhiqiang Dai, Gaochao Xu, Ziqi Liu, Jiaqi Ge and Wei Wang
Unmanned aerial vehicles (UAVs) have the characteristics of portability, safety, and strong adaptability. In the case of a maritime disaster, they can be used for personnel search and rescue, real-time monitoring, and disaster assessment. However, the po...
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Baris Eren Perk and Gokhan Inalhan
To control unmanned aerial systems, we rarely have a perfect system model. Safe and aggressive planning is also challenging for nonlinear and under-actuated systems. Expert pilots, however, demonstrate maneuvers that are deemed at the edge of plane envel...
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Mohammed Hossny, Julie Iskander, Mohamed Attia, Khaled Saleh and Ahmed Abobakr
Continuous action spaces impose a serious challenge for reinforcement learning agents. While several off-policy reinforcement learning algorithms provide a universal solution to continuous control problems, the real challenge lies in the fact that differ...
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