Results 141 to 150 of about 404,230 (315)

Hierarchical Reinforcement Learning Based Resource Allocation for RAN Slicing

IEEE Access
As the complexity of wireless mobile networks increases significantly, artificial intelligence (AI) and machine learning (ML) have become key enablers for radio resource management and orchestration.
Hasan Anil Akyildiz, Omer Faruk Gemici, Ibrahim Hokelek, Hakan Ali Cirpan   +3 more
doaj   +1 more source

An LEO Constellation Early Warning System Decision-Making Method Based on Hierarchical Reinforcement Learning. [PDF]

Sensors (Basel), 2023
Cheng Y, Wei C, Sun S, You B, Zhao Y.
europepmc   +1 more source

Cancer‐Associated Fibroblasts Functions as Multifunctional Architects of the Tumor Stroma and Represent Emerging Therapeutic Vulnerabilities

Advanced Science, EarlyView.
ABSTRACT Cancer‐associated fibroblasts (CAFs) are the predominant stromal components within the tumor microenvironment (TME), playing multifaceted roles in cancer progression through dynamic interactions with neoplastic and immune cells. Emerging evidence has revealed remarkable heterogeneity and plasticity of CAFs, which originate from diverse ...
Rujiao Liu, Lili Su, Shuiping Gao, Wenting Liu, Hongxia Wang   +4 more
wiley   +1 more source

Subgoals in Hierarchical Reinforcement Learning

Hierarchy is an important feature of efficient cognition, including learning and reasoning. In the hierarchical reinforcement learning framework, complex learning problems are decomposed into sub-components that lead to subgoals; subgoals can, in turn, be flexibly combined and used to solve a problem in the absence of immediate rewards.
Milena Rmus, Maria K. Eckstein, Anne Collins   +2 more
openaire   +1 more source

Hierarchical Reinforcement Learning, Sequential Behavior, and the Dorsal Frontostriatal System. [PDF]

J Cogn Neurosci, 2022
Janssen M, LeWarne C, Burk D, Averbeck BB.   +3 more
europepmc   +1 more source

Hierarchical Summary Statistics Encoding Across Primary Visual and Posterior Parietal Cortices

Advanced Science, EarlyView.
This study shows that mouse V1 simultaneously encodes the ensemble mean and variance of motion, providing a robust summary‐statistic representation that persists despite single‐neuron variability. These signals propagate to PPC, where they are transformed into abstract category representations during decision making.
Young‐Beom Lee, Oliver James, Gaeun Jung, Doyun Lee, Yee‐Joon Kim   +4 more
wiley   +1 more source

Goal-oriented hierarchical reinforcement learning-based overlay multicast routing method with SDN integration

Tongxin xuebao
Traditional overlay multicast lacks effective awareness of underlying network states and adaptability to dynamic network conditions. Meanwhile, existing reinforcement learning–based routing methods often suffer from unstable learning and slow convergence
Ye Miao, Li Fanyou, Wen Peng, Jiang Qiuxiang, Wang Yong, He Qian, Ye Cong   +6 more
doaj  

Hierarchical & Factored Reinforcement Learning

, 2010
Cette thèse a été réalisée dans un contexte de simulation industrielle qui s'intéresse aux problèmes de la modélisation du comportement humain dans les simulateurs d'entraînement militaire ou de sécurité civile. Nous avons abordé cette problématique sous l'angle de l'apprentissage et de la planification dans l'incertain, en modélisant les problèmes que
openaire   +1 more source

The Mitochondrial Guardian α‐Amyrin Mitigates Alzheimer's Disease Pathology via Modulation of the DLK‐SARM1‐ULK1 Axis

Advanced Science, EarlyView.
Dietary habits play a key role in chronic diseases, and higher annual consumption of fruit and vegetable may lower risk of dementia. Artificial intelligence predicts the lipid‐like compound α‐Amyrin (αA) from plants with edible peels as a drug candidate against Alzheimer's disease.
Shu‐Qin Cao, Juan Ignacio Jiménez‐Loygorri, Yunguang Qiu, You Jung Kang, Khanh Van Do, Annabel E. Smith, Junjie Huang, Jun‐ping Pan, Lipeng Mao, Ang Li, Hangge Yang, Yahyah Aman, Maria Jose Donate Lagartos, Sofie Hindkjær Lautrup, Anbin Chen, Kristina Xiao Liang, Hailong Zhang, Juan Yi, Xurui Jin, Tin Cho Cheung, Olympia Apokotou, Florentia Papastefanaki, Rebecca Matsas, William A. McEwan, Feixiong Cheng, Hansang Cho, Guobing Chen, Huanxing Su, Konstantinos Palikaras, Oscar Junhong Luo, Qian Hua Zhao, Ding Ding, Cornelia van Duijn, Nektarios Tavernarakis, Patricia Boya, Tewin Tencomnao, Evandro F. Fang   +36 more
wiley   +1 more source

Toward an Adaptive Threshold on Cooperative Bandwidth Management Based on Hierarchical Reinforcement Learning. [PDF]

Sensors (Basel), 2021
Mobasheri M, Kim Y, Kim W.
europepmc   +1 more source