Abstract: This study introduces a novel finite time fault tolerant controller integrating nonsingular terminal sliding mode (NTSM) and reinforcement learning (RL) strategies for manipulator systems ...

Abstract: The traveling salesman problem (TSP) has long been a central focus in combinatorial optimization, with extensive applications in areas such as logistics and transportation. With the rapid ...

Welcome to drlzh.ai: the most hands-on reinforcement learning experience! This course is a deep dive into the vast and evolving world of Deep Reinforcement Learning, split into two parts. First, ...

Causal Reinforcement Learning (CRL) is a suite of algorithms, embedding causal knowledge into RL for more efficient and effective model learning, policy evaluation, or policy optimization. How ...

Discover how OpenAI's ChatGPT Codex can automate, debug, and manage your code effortlessly, saving time and boosting ...

The bird has never gotten much credit for being intelligent. But the reinforcement learning powering the world’s most advanced AI systems is far more pigeon than human. In 1943, while the world’s ...