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Artificial intelligence (AI), including machine learning, deep learning, reinforcement learning, and generative AI, has the potential to advance critical care nephrology (CCN) by enhancing prediction accuracy, improving ...

Chiral nanostructures can enhance the weak inherent chiral effects of biomolecules and highlight the important roles in chiral detection. However, the design of the chiral nanostructures is challenged by extensive theore...

Digital twins are increasingly used in wireless networks to provide geometry- and channel-aware replicas that support prediction and control, while large language models (LLMs) offer strong instruction-following capabili...

"What should be the sensing capabilities of agents in a Multi-Agent System be to solve a problem efficiently, quickly and economicly? This question often appears when trying to solve a problem using Multi-Agent Systems. ...

Dear Readers,It gives me great pleasure to announce the fourth regular issue of 2026. In this issue, 6 papers by 25 authors from 6 countries - Colombia, Greece, Mexico, Republic of Serbia, South Africa, Türkiye ...

Mobility-as-a-Service (MaaS) orchestration faces critical challenges in managing the Service Quality Index (SQI), Fleet Utilization Ratio (FUR), and Dynamic Pricing Index (DPI) under uncertain and time-varying urban dema...

The rapid adoption of AI chatbots for emotional support and quasi-therapeutic interaction raises questions that existing clinical and regulatory frameworks are not equipped to address. This Perspective applies the psychi...

As the nexus between aviation, fire science, and emergency management becomes increasingly more complex, technology can be used to augment training and avoid risk while maintaining authenticity with situational reality. ...

Academic goals and academic self-attributions are relevant variables in school settings. The objective of this study is to identify whether there are combinations of multiple goals that lead to different motivational pro...

Q-Learning is a Reinforcement Learning method for solving sequential decision problems, where the utility of actions depends on a sequence of decisions and there exists uncertainty about the dynamics of the environment t...

Materias / palabras clave: Artificial intelligence; Deep learning; Computer science; Artificial neural network; Backpropagation; Reinforcement learning; Machine learning; Deep neural networks; Unsupervised learning; Recurrent neural network; Encod...

The proceedings of the 2001 Neural Information Processing Systems (NIPS) Conference. The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. The conference ...

The long-anticipated revision of this #1 selling book offers the most comprehensive, state of the art introduction to the theory and practice of artificial intelligence for modern applications. Intelligent Agents. Solvin...

Cache-coherent, nonumiform memory acces or cc-NUMA is an attractive architecture for building a spectrum of shared memory multiprocessors (whic are socing widespread use in commercial, technical and scientific applicatio...

Materias / palabras clave: Monte Carlo tree search; Computer science; Champion; Artificial neural network; Reinforcement learning; Artificial intelligence; Game tree; Value (mathematics); Search algorithm; Tree (set theory); Deep neural networks; ...

Materias / palabras clave: Champion; Artificial intelligence; Artificial neural network; Reinforcement learning; Computer science; Selection (genetic algorithm); Tree (set theory); Machine learning; Domain (mathematical analysis); Mathematics; Pol...

Options have been shown to be a key step in extending reinforcement learning beyond low-level reactionary systems to higher-level, planning systems. Most of the options research involves hand-crafted options; there has b...

"Error-related potential (ErrP) are a particular type of Event-Related Potential (ERP) elicited by a person attending a recognizable error. These Electroencephalographic (EEG) signals can be used to train a gaming agent ...

Papers from the 2006 flagship meeting on neural computation, with contributions from physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The annual Neural Information Processing Systems (...

We propose a technique for producing `visual explanations' for decisions from a large class of Convolutional Neural Network (CNN)-based models, making them more transparent. Our approach - Gradient-weighted Class Activat...

Materias / palabras clave: machine learning, artificial intelligence, computational physics, reinforcement learning, neural networks, applied algorithms; Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer e...

Materias / palabras clave: machine learning, neural networks, reinforcement learning, control theory, ai driven automation, learning driven decision; Technology: Mechanical engineering and machinery: Control engineering systems. Automatic machiner...

Materias / palabras clave: artificial intelligence, deep learning, machine learning, pattern recognition, artificial neural networks, reinforcement learning; Science: Mathematics: Instruments and machines: Electronic computers. Computer science

Materias / palabras clave: control and optimization, process control, optimization, artificial intelligence, reinforcement learning, computer simulation; Technology: Technology (General): Industrial engineering. Management engineering: Applied mat...