A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source
Exploring equity in global health collaborations: a qualitative study of donor and recipient power dynamics in Liberia. [PDF]
Cakouros BE +6 more
europepmc +1 more source
Autonomy, power dynamics and antibiotic use in primary healthcare: A qualitative study. [PDF]
Medina-Perucha L +10 more
europepmc +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +2 more
wiley +1 more source
Governance of the wildlife trade and the prevention of emerging zoonoses: a mixed methods network analysis of transnational organisations, silos, and power dynamics. [PDF]
Clifford Astbury C +11 more
europepmc +1 more source
β‐Catenin/c‐Myc Axis Modulates Autophagy Response to Different Ammonia Concentrations
Ammonia, detoxified by the liver into urea and glutamine, impacts autophagy differently at varying levels. Low ammonia activates autophagy via c‐Myc and β‐catenin, while high levels suppress it. Using Huh7 cells and Spf‐ash mice, c‐Myc's role in cytoprotective autophagy is revealed, offering insights into hyperammonemia and potential therapeutic ...
S. Sergio +11 more
wiley +1 more source
Through the Zoom window: How children use virtual technologies to navigate power dynamics in research. [PDF]
Fechtel H +5 more
europepmc +1 more source
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Low‐cycle fatigue damage in Mn–Mo–Ni reactor pressure vessel steel is examined using a combined electron backscatter diffraction and positron annihilation lifetime spectroscopy approach. The study correlates texture evolution, dislocation substructure development, and vacancy‐type defect formation across uniform, necked, and fracture regions, providing
Apu Sarkar +2 more
wiley +1 more source

