Blueprint embeds explainability into AI systems from the ground up
Researchers propose a modular multi-agent framework, SoS-ML, that generates evidence-based explanations from internal model representations rather than post-hoc justifications.
Researchers propose a modular multi-agent framework, SoS-ML, that generates evidence-based explanations from internal model representations rather than post-hoc justifications.
Researchers have built a MetaGPT-based multi-agent AI framework that combines mix-augmented generation with activation-aware weight quantization to deliver fast, accurate ...
A new multi-agent AI system called MATE uses specialized debating agents and a coordinating agent to score essays across multiple ...
A new fuzzy multi-agent framework continuously assesses hospital resource health and detected simulated degradation about 69 hours earlier than a ...
A diagnostic study of 100 de-identified legal consultations found that multi-agent AI generated usable but variably evaluated factual narratives, with ...
A new MARL framework guided by MPC expert knowledge achieves coordinated frequency control across interconnected microgrids, with pass rates up ...
A new multi-agent AI framework called PentestMCP autonomously conducts full penetration testing campaigns, achieving up to 87.2 percent success in ...
A multi-agent AI system combining large language models, knowledge graph embeddings, and collaborative agents reads power grid alarm rules, recognizes ...
Researchers in Japan have developed a communication-free shepherding algorithm that lets multiple steering agents guide passive flocks using only local ...
A new editorial in Frontiers in Control Engineering surveys how game theory, graph neural networks, and heterogeneous robot teams are ...
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© 2025 Scienmag - Science Magazine