多智能体
18 篇 · 资讯流Multi-Objective Reinforcement Learning Using Routed Ensembles and Trajectory Attribution
Multi-objective reinforcement learning is a fundamental problem for modern AI, with applications spanning post-training,
原文 ↗Multimodal Embodied Agents: A Unified Capability-centric Perspective from Computer-Use to Robot-Use
Multimodal agents (MMAs) sustain interaction through reasoning, memory, tools, and feedback, most visibly as computer-us
原文 ↗Conflicted Records: Typed Adversarial Contracts for Auditable LLM Output Quality Enforcement
LLM-generated records increasingly populate production information systems where they are treated as data assets subject
原文 ↗Local Work, Global Progress: A Convergence Theory of AI Agent Collaboration
Teams of large language model (LLM) agents are increasingly applied to complex tasks, but their collaboration protocols
原文 ↗Bidirectionality is Necessary in Cellular Machines for Exact-Arrival Multi-Agent Path Finding
On ranked directed acyclic graphs coupled by vertex conflicts we study exact-arrival multi-agent path finding (departure
原文 ↗Auditable and Deployable Multi-Agent Motion Planning via Posetal Games from Legal Guidelines
When robots are deployed in the real-world, they must interact with other agents and accomplish their own goals while ad
原文 ↗MARGoS: A Configuration-Driven Platform for Reproducible MARL Experiments in ARGoS
Multi-agent reinforcement learning (MARL) has become a prominent research direction, particularly within collective robo
原文 ↗Visual Swarm Navigation via Deep Reinforcement Learning and Evolutionary Hybrid Design
Swarm robotics presents a robust and cost-effective paradigm for advanced automation in complex, dynamic environments, s
原文 ↗EdgeAgent: Orchestrating On-Device LLM inference for End-User Multi-Agent Systems on CPU-GPU Unified Memory Architectures
Emerging multi-agent LLMs demand privacy-preserving edge deployment, yet current inference systems struggle with these c
原文 ↗Managing Context and Communication in Distributed Agentic UAV Swarms
Unmanned aerial vehicle (UAV) swarms increasingly rely on language-model agents to provide adaptive mission-level reason
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