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

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

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

Understanding intelligence and creating intelligent machines are grand scientific challenges of our times. The ability to ...

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 ...

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.

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

AI agents develop their own communication channels beyond our monitoring frameworks, we face a pivotal challenge: harnessing ...

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 ...