Abstract: The resolution of proof-of-work problem in blockchain requires significant amount of resources, while the lack of computing power on mobile devices limits the development of blockchain in ...

Extreme events such as earthquakes can readily cause structural damage and operational disturbances in power grids, thereby weakening the system’s supply stability and recovery capability and posing ...

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

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 ...

Optimizing the operation of interconnected hydropower systems presents significant challenges due to complex non-linear dynamics, hydrological uncertainty, and the need to balance competing objectives ...

Abstract: In the digital realm, ensuring the security and reliability of systems and software is of paramount importance. Fuzzing has emerged as one of the most effective testing techniques for ...

Enhancing heat transfer in turbulent flows is vital for energy systems and industrial processes, yet conventional methods yield limited gains. We demonstrate how artificial intelligence autonomously ...

Reinforcement Learning implementation to generate parameters of sinusoidal curves that, through an LQR and Proportional controller, generate the angles for a simulated robot to walk ...