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 ...

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 ...

"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 ...

In 2026, enterprises will be expected to automate processes that involve judgment, negotiation, compliance interpretation, ...

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 ...

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

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 ...