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

Reinforcement Learning is a powerful approach to machine learning that enables agents to learn optimal behaviors through ...

Reinforcement learning designs intelligent agents by training them to maximize rewards as they interact with their ...

Agentic AI has emerged as the latest permutation of generative AI, enabling autonomous functionality as a way to deliver business value. But how the agents work can be a bit of a mystery.

There has been much talk about how AI could recursively self-improve in the coming years, but it appears that Google ...

By categorizing and filtering user input, you can better focus on driving AI improvement. This iterative process—blending automation with human review—ensures AI learns from high-quality data, leading ...

In the ever-evolving world of artificial intelligence (AI), the ability to make effective decisions is a cornerstone of ...

Enhancing Microsoft CyberBattleSim for Enterprise Cybersecurity Simulations. Journal of Information Security, 16, 270-282. doi: 10.4236/jis.2025.162014 . Quantifying the effectiveness of cyber defense ...

Reinforcement Learning (RL) is a type of machine learning where a model learns to make decisions by interacting with an environment. Unlike supervised learning, where the model is provided with ...

AI agents can be found in a variety of industries, including healthcare, finance, manufacturing, customer service, and ...