A new AI model learns to "think" longer on hard problems, achieving more robust reasoning and better generalization to novel, unseen tasks.

This article considers irrigation canal control problems where human agents are free to move along the canal temporarily overriding the position of actuators, which are considered to be ...

Finite control set-model predictive control (FCS-MPC) operates based on the assumption that optimal control responses executed on a prediction model match closely an actual system. Thus, model ...

This study introduces a Q-learning-based nonlinear model predictive control (QL-NMPC) framework for temperature control in batch reactors. A reinforcement learning agent is trained in simulation to ...