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 ...

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 ...

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

Kimi K2.5 introduces a multi-agent orchestration with up to 100 workers, helping teams cut complex task time and boost ...

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 ...

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 ...

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 ...

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 ...