Deep Reinforcement Learning for Secure and Low-Latency Communications in UAV-Mounted STAR-RIS Assisted Urban Vehicular Networks. [PDF]
Tang J, Yuan J, Zhao H, Chen M, Peng Y.
europepmc +1 more source
Modeling and Simulating Complex Conflict Management Using Reaction Networks. [PDF]
Veloz T, Bruin D, De Coning C.
europepmc +1 more source
Tracheal chambers as a key innovation for high‐frequency emission in bat echolocation
Abstract Key innovations are pivotal for biodiversity and facilitating evolutionary success, enabling organisms' adaptation to various ecological niches through the diversification of phenotypic traits. In mammals, notable adaptations include evolving hypsodonty for grazing on grasses and, for bats, evolving echolocation and wing acquisition.
Nicolas L. M. Brualla +7 more
wiley +1 more source
Cooperative UAV swarms for zero knowledge verification of edge generative AI using trust-aware multiagent learning. [PDF]
Avazov K +6 more
europepmc +1 more source
Evolutionary morphology of the haplorhine hamate
Abstract Primates adopt a variety of hand postures during an impressive diversity of locomotor and manipulative behaviors. Morphological research has found that elements of the hand skeleton, such as the hamate, hold key information for inferring hand use and locomotor kinematics in extinct species.
Laura E. Hunter +4 more
wiley +1 more source
HH-MAPPO: A Hierarchical Reinforcement Learning Framework for Dynamic-Scale Target-Attacker-Defender Games. [PDF]
Huang J +6 more
europepmc +1 more source
Abstract Cross‐disciplinary research is a priority for many academic institutions, with a growing body of scholarship dedicated to studying the central practice of cross‐disciplinarity: integration, or the synthesis of knowledge, information, and data across disciplines and domains.
Ciara Zogheib
wiley +1 more source
A cognitive internet of things resource allocation method based on multi-agent reinforcement learning algorithm. [PDF]
Wang R, Shen Y, Wang D, Li W.
europepmc +1 more source
ABSTRACT The synchronization accuracy between the wafer stage and reticle stage in lithography is critical to overlay and critical dimension uniformity. Existing iterative learning control (ILC) methods indirectly optimize synchronization via time‐domain errors, failing to balance low‐frequency tracking accuracy and high‐frequency noise suppression ...
Xin Zhou +4 more
wiley +1 more source
Behavior-aware deep reinforcement learning for multi-objective outpatient scheduling optimization. [PDF]
Wan X, Zhang X, Weng W, Han P, Xu X.
europepmc +1 more source

