ABSTRACT: Oracle-based quantum algorithms cannot use deep loops because quantum states exist only as mathematical amplitudes in Hilbert space with no physical substrate. Critically, quantum wave ...

Explore the reinforcement learning algorithm that achieves performance comparable to GRPO in RLVR with minimal complexity. Learn how it works, why it’s effective, and its practical applications in RL ...

Choose the appropriate .yml file for your system. These Anaconda environments use MuJoCo 1.5 and gym 0.10.5. You'll need to get your own MuJoCo key if you want to use ...

In reinforcement learning (RL), an agent learns to achieve its goal by interacting with its environment and learning from feedback about its successes and failures. This feedback is typically encoded ...

Researchers at Google have developed a technique that makes it easier for AI models to learn complex reasoning tasks that usually cause LLMs to hallucinate or fall apart. Instead of training LLMs ...

Abstract: The Python Testbed for Federated Learning Algorithms is a simple Python FL framework that is easy to use by ML&AI developers who do not need to be professional programmers and is also ...

Wind turbine control systems have evolved significantly over the past decades, moving from simple classical controllers to sophisticated artificial intelligence-based strategies. Early utility-scale ...

The path planning capability of autonomous robots in complex environments is crucial for their widespread application in the real world. However, long-term decision-making and sparse reward signals ...

Abstract: Taking advantage of their data-driven and model-free features, Deep Reinforcement Learning (DRL) algorithms have the potential to deal with the increasing level of uncertainty due to the ...

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...

Researchers at the University of Science and Technology of China have developed a new reinforcement learning (RL) framework that helps train large language models (LLMs) for complex agentic tasks ...

How do you keep reinforcement learning for large reasoning models from stalling on a few very long, very slow rollouts while GPUs sit under used? a team of researchers from Moonshot AI and Tsinghua ...