AI & Machine Learning · Computer Science & AI
Multiagent Systems
The newest papers in Multiagent Systems that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
829 papers, from 4 September 2026 to 5 November 2026: 829 arXiv preprints.
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Newest papers, page 26
ActiveSaddler: Automated Curriculum Learning for Agent Harness Optimization
Automated harness optimization can substantially improve LLM agents by iteratively updating their prompts, tool interfaces, and control logic from execution feedback.VeriHarness: Scaling Agentic Verification for Long-Horizon Tasks
As LLM agents undertake increasingly complex, long-horizon tasks, verifying their outputs becomes increasingly challenging.Can AI Scientists Coordinate at Runtime?
Multi-agent AI scientists have shown improving performance across a diverse range of tasks.MASkillBlender: Decentralized Whole-Body Coordination for Multi-Humanoid Loco-Manipulation via Skill Blending
Coordinated multi-humanoid loco-manipulation is promising yet challenging due to high-dimensional whole-body control, decentralized decision making, and scalability.Fully Online Decentralized Learning in Stochastic Games with Unknown Independent Chains
We consider stochastic games with independent controlled chains and unknown transition kernels, where players observe only their local states and realized payoffs.LLM-Driven Multi-Agent Control for Skill-Based Smart Manufacturing
Factories are shifting toward smaller lot sizes with high product customization, requiring frequent re-programming of flexible and reconfigurable automation systems.A Multi-Agent LLM Framework for Personalized Health Checkup Interpretation and Guidance
Personalized interpretation of health checkup results requires reasoning across longitudinal records, medical knowledge, lifestyle guidance, and healthcare navigation.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 reasoning in uncertain environments.After Cooperation Is Learned: Gradient Routing and Optimizer-Dependent Maintenance in Multi-Agent Reinforcement Learning
Cooperative MARL is commonly evaluated through cooperation discovery from random initialization, leaving open whether continued optimization can destabilize learned cooperation.SoK: Decentralized Agent Economic Infrastructure
Decentralized agent economies increasingly build a single task from protocols that were designed and secured separately.Token Communication-Assisted Collaborative Embodied Artificial Intelligence: Concepts, Framework, and Opportunities
Collaborative embodied artificial intelligence (CEAI) enables multiple physical agents to perceive, reason, and act cooperatively in dynamic environments.Form and Void: Entangled Composition through an Autonomous AI Agent
Positive and negative space is a fundamental principle in visual composition, supporting visually coherent forms and layered semantic relationships.Decentralized Power-Optimal Coordination for Spacecraft Swarms Using Time-Varying Magnetorquer Actuation
This paper presents a decentralized power-optimal coordination framework for magnetically actuated spacecraft swarms.Watch, Infer, Coordinate: Inferring Robot Partner Constraints for Zero-Shot Coordination
Robots operating in the physical world will increasingly need to coordinate with other robots, particularly in manipulation tasks where an object may be too large or heavy for a single robot to…MIRROR: Multipath Quorum Integrity for LLM Multi-Agent Communication
Inter-agent communication is central to Large Language Model Multi-Agent Systems (LLM-MAS), but it introduces an underexplored vulnerability: Agent-in-the-Middle (AiTM) attacks that manipulate…Decentralized Decision-Making among Heterogeneous Autonomous Vehicles: An $α$-Potential Game Framework
We study noncooperative multi-vehicle games among heterogeneous autonomous vehicles, where each vehicle adopts a decentralized closed-loop policy based on its own state, and optimizes an objective…Where Do Multi-Agent Systems Fail? Evidence-Grounded Diagnosis of Collective Mechanisms
When a multi-agent system answers correctly, it is tempting to conclude that its agents shared, checked, and used information as intended.SkillSeek: Revisiting Agent Skill Retrieval at Marketplace Scale
Anthropic's Agent Skills package reusable procedural know-how for an LLM agent into SKILL.md directories, and open-source aggregations have grown past 230,000 skills, making selection rather than…Risk-Aware Adaptive Evaluation: Finding High-Impact Failures Under Limited Budgets
Evaluating interactive agents is expensive.Fast and Scalable Multi-Agent Distribution Matching via Partitioned Optimal Transport
This paper presents a scalable optimal-transport-based framework for terminal distribution matching in multi-agent systems.