Nature

A traffic light control method based on multi-agent deep reinforcement learning algorithm

Intelligent traffic light control (ITLC) algorithms are very efficient for relieving traffic congestion. Recently, many decentralized multi-agent traffic light control algorithms are proposed. These ...
Nature

A multi-agent reinforcement learning scheduling algorithm integrating state graph and task graph structural modeling for ride-sharing dispatching

Urban-scale ride-hailing dispatch faces critical challenges such as heterogeneous demand density, highly dynamic state transitions, and multi-agent coordination. Traditional rule-based or heuristic ...
EurekAlert!

A new AI-based attack framework advances multi-agent reinforcement learning by amplifying vulnerability and bypassing defenses

Researchers have developed a new artificial intelligence approach that exposes critical weaknesses in multi-agent reinforcement learning systems, enabling stronger coordinated attacks with broad ...
Forbes

The Rise And Rise Of Reinforcement Learning: AI’s Quiet Revolution

Forbes contributors publish independent expert analyses and insights. Author, Researcher and Speaker on Technology and Business Innovation. Apr 19, 2025, 03:24am EDT Apr 21, 2025, 10:40am EDT ...
VentureBeat

Google finds that AI agents learn to cooperate when trained against unpredictable opponents

Training standard AI models against a diverse pool of opponents — rather than building complex hardcoded coordination rules — is enough to produce cooperative multi-agent systems that adapt to each ...