Computational intelligence and neuroscience
Jun 24, 2022
In the shortest path planning problem, the old algorithm usually has many defects, such as the robot's cognition being contrary to reality, the lack of practical operation feasibility, or the limitation of problem processing. Nowadays, with deep lear...
Journal of chemical information and modeling
Jun 16, 2022
Reinforcement machine learning is implemented to survey a series of model potential energy surfaces and ultimately identify the global minima point. Through sophisticated reward function design, the introduction of an optimizing target, and incorpora...
IEEE transactions on cybernetics
Jun 16, 2022
In this article, a decentralized adaptive optimal controller based on the emerging mean-field game (MFG) and self-organizing neural networks (NNs) has been developed for multiagent systems (MASs) with a large population and uncertain dynamics. This d...
IEEE transactions on cybernetics
Jun 16, 2022
Deep reinforcement learning (DRL) recently has attained remarkable results in various domains, including games, robotics, and recommender system. Nevertheless, an urgent problem in the practical application of DRL is fast adaptation. To this end, thi...
Sensors (Basel, Switzerland)
Jun 7, 2022
Agricultural robots are one of the important means to promote agricultural modernization and improve agricultural efficiency. With the development of artificial intelligence technology and the maturity of Internet of Things (IoT) technology, people p...
Proceedings of the National Academy of Sciences of the United States of America
May 27, 2022
Adolescent development is characterized by an improvement in multiple cognitive processes. While performance on cognitive operations improves during this period, the ability to learn new skills quickly, for example, a new language, decreases. During ...
Sensors (Basel, Switzerland)
May 19, 2022
Autonomous navigation in dynamic environments where people move unpredictably is an essential task for service robots in real-world populated scenarios. Recent works in reinforcement learning (RL) have been applied to autonomous vehicle driving and t...
IEEE transactions on cybernetics
May 19, 2022
Encouraging the agent to explore has always been an important and challenging topic in the field of reinforcement learning (RL). Distributional representation for network parameters or value functions is usually an effective way to improve the explor...
Scientific reports
May 18, 2022
Career planning consists of a series of decisions that will significantly impact one's life. However, current recommendation systems have serious limitations, including the lack of effective artificial intelligence algorithms for long-term career pla...
IEEE transactions on neural networks and learning systems
May 2, 2022
Bin-packing problem (BPP) is a typical combinatorial optimization problem whose decision-making process is NP-hard. This article examines BPPs in varying environments, where random number and shape of items are to be packed in different instances. Th...