Multi-Agent Reinforcement Learning (MARL) is an emerging subfield of artificial intelligence that investigates how multiple autonomous agents can learn collaboratively and competitively within an ...

This collection supports and amplifies research related to SDG 4: Quality Education. Generative AI is transforming the conventional dyadic teacher-student dynamic into a triadic framework centered ...

Welcome to the world of RDHNet, a groundbreaking approach to multi-agent reinforcement learning (MARL) introduced by Dongzi Wang and colleagues from ...

The overall relationship between the attacker and the ego system. The black solid arrows indicate the direction of data flow, the red solid ones indicate the direction of gradient flow and the red ...

The biggest challenge to AI initiatives is the data they rely on. More powerful computing and higher-capacity storage at lower cost has created a flood of information, and not all of it is clean. It ...

Artur Schweidtmann says multi-agent systems can reshape the way engineers design and operate chemical plants – turning AI into collaborative digital teammates rather than replacements ...

Large language models like ChatGPT play an ever-evolving role in the modern business landscape. Your curiosity may have led you to engage two AI models in conversation before, but have you considered ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The age-old game of hide-and-seek can reveal a lot about how AI weighs ...

AI agents are currently at the cutting-edge of how we are using AI to tackle complex tasks and decision-making processes. These autonomous systems, designed to operate without human intervention, are ...