The review introduces a proposed two-layer reinforcement learning framework for distributed smart grid control. In this ...

Model instability: RL models, especially when used with neural networks (as in deep reinforcement learning), can be unstable during training, requiring careful tuning of hyperparameters to avoid ...

and multi-agent reinforcement learning methods. The experimental results were promising. The IPPO method outperformed the other methods in terms of convergence and solution quality. It achieved ...

and ready access to data and simulation tools have helped make Deep Reinforcement Learning one of the most powerful tools for dealing with control-driven dynamic systems today. From the design of ...

In the evolving world of algorithmic trading, innovation is critical for maintaining an edge in the markets. Ramprasad Reddy Mittana, an expert in the field, highlights how the fusion of human ...

In an era where cloud-native architectures are at the forefront of digital transformation, regulatory compliance has become ...

In the field of wireless communication, security is of utmost importance. A new study published in Engineering explores ...

A recent study in Engineering presents LearningEMS, a unified framework and open-source benchmark for electric vehicle (EV) ...