Formulation and solution of applicable optimization models, including linear, integer, nonlinear, and network problems. Efficient algorithmic methods and use of oomputer modeling languages and systems ...

This study seeks to construct a basic reinforcement learning-based AI-macroeconomic simulator. We use a deep RL (DRL) approach (DDPG) in an RBC macroeconomic model. We set up two learning scenarios, ...

The whole picture of Mathematical Modeling is systematically and thoroughly explained in this text for undergraduate and graduate students of mathematics, engineering, economics, finance, biology, ...

Epshtein argues that a deeper understanding of generalization and principled use of prior knowledge are essential to building ...

On stage, at NVIDIA GTC 2026, Marketeam.ai unveiled RL-KPI (Reinforcement Learning with Key Performance Indicators), a ...

The AI industry is shifting its focus from building larger models to ensuring their reliable operation, according to Satya ...