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 ...

Researchers have developed a novel framework, termed PDJA (Perception–Decision Joint Attack), that leverages artificial ...

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 College of Computer Science at the National ...

Learn Google Antigravity, a free AI IDE with an Agent Manager and Artifacts view, so you automate workflows faster and avoid ...

Microsoft researchers have unveiled a new open source multi-agent AI system, aimed to help enterprises automate complex tasks typically requiring human intervention. Named Magnetic-One, the project is ...

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 ...

What if the very systems designed to transform problem-solving are quietly failing behind the scenes? Multi-agent AI, often hailed as the future of artificial intelligence, promises to tackle complex ...