Abstract: Inverse reinforcement learning optimal control is under the framework of learner–expert, the learner system can learn expert system's trajectory and optimal control policy via a ...

Austin, Texas, United States, December 22nd, 2025, FinanceWire Safe Pro Group (NASDAQ: SPAI) today announced the deployment ...

Unmanned surface vehicles (USVs) nowadays have been widely used in ocean observation missions, helping researchers to monitor climate change, collect environmental data, and observe marine ecosystem ...

This important study uses reinforcement learning to study how turbulent odor stimuli should be processed to yield successful navigation. The authors find that there is an optimal memory length over ...

CML unlocks AI’s full potential with enhanced pattern recognition, prediction and real-time decision-making for defense, autonomous systems and next-gen computing. Infleqtion, a global leader in ...

Abstract: This paper studies a deep reinforcement learning technique for distributed resource allocation among cognitive radios operating under an underlay dynamic spectrum access paradigm which does ...

Reinforcement learning (RL) trains agents to make sequential decisions by maximizing cumulative rewards. It has diverse applications, including robotics, gaming, and automation, where agents interact ...

The year 2024 is the time when most manual things are being automated with the assistance of Machine Learning algorithms. You’d be surprised at the growing number of ML algorithms that help play chess ...