Abstract: In this letter, we address the problem of behavior-based cooperative navigation of mobile robots usingsafe multi-agent reinforcement learning (MARL). Our work is the first to focus on ...

Inside Claude-Flow: Using Multi-Agent AI to Modernize Legacy Applications Faster Your email has been sent Multi-agent AI orchestration frameworks like Claude-Flow help teams modernize legacy ...

Abstract: Although Multi-Agent Reinforcement Learning (MARL) is effective for complex multi-robot tasks, it suffers from low sample efficiency and requires iterative manual reward tuning. Large ...

Cursor has for the first time introduced what it claims is a competitive coding model, alongside the 2.0 version of its integrated development environment (IDE) with a new feature that allows running ...

Download PDF Join the Discussion View in the ACM Digital Library Deep reinforcement learning (DRL) has elevated RL to complex environments by employing neural network representations of policies. 1 It ...

We propose Tree-GRPO, adopting a tree-search rollout strategy in place of independent chain-based rollouts for LLM agent RL. Based on ReAct step-level nodes, Tree-GRPO carries out rollout sampling ...

What if the future of work wasn’t just about automation but about collaboration, between humans and intelligent agents? Imagine a world where multi-agent AI systems seamlessly coordinate tasks, adapt ...

According to Nvidia’s 2025 State of AI in Financial Services report, one in four firms identify portfolio optimization as the single most ROI generative application of AI in Finance. In reality, ...