A Machine Learning Approach for User Behavior Analysis in Developing Websites by Aeesha Shaheen

Get full text

Adaptive Dynamic Programming with Reinforcement Learning on Optimization of Flight Departure Scheduling by Hong Liu, Song Li, Fang Sun, Wei Fan, Wai-Hung Ip, Kai-Leung Yung

“…This technique harnesses an approximation of the dynamic programming value function, augmented by reinforcement learning to enhance the approximation and alleviate the computational complexity as the number of flights increases. …”
Get full text

Near real-time online reinforcement learning with synchronous or asynchronous updates by Mircea-Bogdan Radac, Darius-Pavel Chirla

“…Abstract Reinforcement Learning (RL) is a well-known method for learning control of complex and unknown dynamical systems. …”
Get full text

Road-Adaptive Precise Path Tracking Based on Reinforcement Learning Method by Bingheng Han, Jinhong Sun

“…In the second layer, we carefully designed the evaluation function in the tracking process based on the uncertainties and performance requirements that may occur during vehicle driving. …”
Get full text

A Gradient-Based Reinforcement Learning Algorithm for Multiple Cooperative Agents by Zhen Zhang, Dongqing Wang, Dongbin Zhao, Qiaoni Han, Tingting Song

“…Multi-agent reinforcement learning (MARL) can be used to design intelligent agents for solving cooperative tasks. …”
Get full text

Imitation-Reinforcement Learning Penetration Strategy for Hypersonic Vehicle in Gliding Phase by Lei Xu, Yingzi Guan, Jialun Pu, Changzhu Wei

“…To enhance the penetration capability of hypersonic vehicles in the gliding phase, an intelligent maneuvering penetration strategy combining imitation learning and reinforcement learning is proposed. Firstly, a reinforcement learning penetration model for hypersonic vehicles is established based on the Markov Decision Process (MDP), with the design of state, action spaces, and composite reward function based on Zero-Effort Miss (ZEM). …”
Get full text

Deep Reinforcement Learning for Vectored Thruster Autonomous Underwater Vehicle Control by Tao Liu, Yuli Hu, Hui Xu

“…In this paper, we propose a controller based on deep reinforcement learning (DRL) in a simulation environment for studying the control performance of the vectored thruster AUV. …”
Get full text

Levo-Stepholidine as a Potential Cognitive Enhancer: Insights into Executive Function and Memory Improvements by Zhengwei Hu, Xueqing Zhu, Yirui Liang, Yuqiu Zhang, Ping Zheng, Xuehan Zhang

“…Here, we investigated the impact of l-SPD on two core indexes of executive function, working memory and response inhibition, and learning and memory. …”
Get full text

Integrated transcriptomic and functional modeling reveals AKT and mTOR synergy in colorectal cancer by Marcin Duleba, Eliza Zimoląg, Joanna Szuszkiewicz, Marcin Serocki, Joanna Szklarczyk, Olga Dracz, Alexander Kurzejamski, Izabella Więckowska, Marcelina Chmiel, Barbara Lipert, Katarzyna Sarad, Joanna Krawczyk, Oleksii Bryzghalov, Agata Stachowicz-Wałaszek, Karolina Pyziak, Joanna Drozdowska, Krzysztof Baczyński, Konrad Wojtowicz, Maurycy Chronowski, Krzysztof Rataj, Magdalena Otrocka, Michał Mikula, Paula Feliksiak, Rafał Dziadziuszko, Tomasz Rzymski, Andrew Thomason, Krzysztof Brzózka, Andrzej Mazan

Get full text

Using Nearest-Neighbor Distributions to Quantify Machine Learning of Materials’ Microstructures by Jeffrey M. Rickman, Katayun Barmak, Matthew J. Patrick, Godfred Adomako Mensah

“…From the moments of these distributions, we obtain so-called learning functions that highlight the rate at which the important topological features of a grain-boundary network appear. …”
Get full text

Domain generalization for image classification based on simplified self ensemble learning. by Zhenkai Qin, Xinlu Guo, Jun Li, Yue Chen

“…Specifically, we frame the problem as an optimization process with the objective of minimizing a weighted loss function that balances cross-domain discrepancies and sample complexity. …”
Get full text

Deep brain stimulation on cognition in epilepsy: A concentration on learning and memory by Beibei Shen, Yi Shi, Yanlu Fu, Yina Cao, Yi Wang, Jiajia Fang

“…More than 60 % of epilepsy patients may experience impairment in learning, memory, attention, and executive control. …”
Get full text

Coverage Path Planning Using Actor–Critic Deep Reinforcement Learning by Sergio Isahí Garrido-Castañeda, Juan Irving Vasquez, Mayra Antonio-Cruz

“…By defining a set of observations, states, and a reward function tailored to characteristics of the environment and the desired behavior of the robot, the training process is conducted, resulting in optimized policies for each algorithm. …”
Get full text

A novel deep learning approach to field-road semantic segmentation by Bei Wang, Wenze Wang

“…This study presents a deep learning framework that implements a novel semantic segmentation model designed to segment field-road trajectories, addressing the marked differences in spatial characteristics. …”
Get full text

Online ECG Biometrics for Streaming Data with Prototypes Learning and Memory Enhancement by Kuikui Wang, Na Wang

“…To enhance the discriminative power of to-be-learned sample representations, we introduce two novel modules: bidirectional regression and prototype learning. …”
Get full text

Science Through Machine Learning: Quantification of Post‐Storm Thermospheric Cooling by Richard J. Licata, Piyush M. Mehta, Daniel R. Weimer, Douglas P. Drob, W. Kent Tobiska, Jean Yoshii

“…Abstract Machine learning (ML) models are universal function approximators and—if used correctly—can summarize the information content of observational data sets in a functional form for scientific and engineering applications. …”
Get full text

Intelligent Detection and Recognition of Marine Plankton by Digital Holography and Deep Learning by Xianfeng Xu, Weilong Luo, Zhanhong Ren, Xinjiu Song

“…For randomly selected samples of Copepods, Tunicates and Polychaetes, the results are ideal and acceptable, and a batch detection function is developed for the learning of the system. …”
Get full text

A Skillful Prediction of Monsoon Intraseasonal Oscillation Using Deep Learning by K. M. Anirudh, Prasang Raj, S. Sandeep, Hariprasad Kodamana, C. T. Sabeerali

“…These indices were obtained through an extended empirical orthogonal function analysis conducted on 25 years of daily rainfall anomalies over the Indian region. …”
Get full text

Observing the observer (I): meta-bayesian models of learning and decision-making. by Jean Daunizeau, Hanneke E M den Ouden, Matthias Pessiglione, Stefan J Kiebel, Klaas E Stephan, Karl J Friston

“…Preferences and goals are encoded through a "loss" (or "utility") function, which measures the cost incurred by making any admissible decision for any given (hidden) state of affair. …”
Get full text

Facial Feature Recognition with Multi-task Learning and Attention-based Enhancements by M. Rohani, H. Farsi, S. Mohamadzadeh

“…First, we introduce an age-specific loss function that minimizes the impact of errors in less critical cases while focusing the learning process on accurate age estimation within sensitive age ranges. …”
Get full text