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 ...

In this podcast, Motley Fool contributor Rachel Warren talks with innovation consultant Lorraine Marchand, author of No Fear, No Failure, about the "five Cs" of innovation and how investors can ...

Q-FlexiViT is evaluated on standard intrusion-detection datasets containing multiple attack types and normal traffic. Using ...

IBS Intelligence (IBSi) is the world’s only pure-play Financial Technology focused research, advisory, and fintech news analysis firm, with a 30-year track record and clients globally. We take pride ...

Abstract: In this paper, we propose a reinforcement learning based algorithm for rate-profile construction of Arikan’s Polarization Adjusted Convolutional (PAC) codes. This method can be used for any ...

ABSTRACT: Objective: To develop and validate a machine learning-based risk prediction model for postoperative nausea and vomiting (PONV) following gynecological day hysteroscopy, providing ...

Every game of chess is a dialogue - A test of intention, creativity, and learning that echoes far beyond the board. “Chess Game” isn’t just another web-based chess app; it’s a bold experiment in ...

ABSTRACT: Offline reinforcement learning (RL) focuses on learning policies using static datasets without further exploration. With the introduction of distributional reinforcement learning into ...

Adaptive algorithms have immensely advanced, becoming integral for innovation across multiple industries. These intelligent systems adjust content and strategies to improve the experiences of users by ...