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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Mental-Models for Multi-Agent Systems
Large foundation models have accelerated progress toward general-purpose agents that interact with humans and other agents through language and multimodal signals.Know What You Don't Know: Agentic Data Synthesis by Evolving Generation Space for Closed-Loop Learning
The continued improvement of large language models increasingly depends on synthetic experience, yet effective data synthesis for interactive agents requires not only executable and verifiable…SoftwareGym: Scaling Computer-Use Agent Training with Diverse Synthesized Software Environments
Computer-use agents (CUAs) are rapidly improving, yet synthesizing diverse and reliable software environments at scale remains challenging.Distributed Harmonic-Covariance Feedback for Hole Closure in Planar Robot Swarms
We consider hole closure in a planar multi-agent system whose sensing disks form a time-varying Čech complex.Robust and Scalable UAV-UGV Planning for Aerial Monitoring under Energy and Precedence Constraints
We consider planning for unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) teams in aerial monitoring missions with ordering requirements on the monitoring points to be visited by the…How Do Hardware Faults Manifest Differently in LLM Agents?
We present the first systematic study of the resilience of large language model (LLM) agents to random hardware-induced faults.Minimizing Cumulative Envy in Allocating a Sequence of Items
We study temporal fair division with indivisible goods that arrive sequentially and must be allocated irrevocably.CANDO: Cooperative Agentic Network for Layout Design Optimization
Layout generation for real-world facilities is a challenging problem, requiring reasoning over irregular site boundaries, heterogeneous orientations, access-aware placements, and motion-planning…Multi-Agent Coordination via Support-Preserving Distillation
Offline MARL increasingly relies on generative policies to model multimodal joint behavior, typically by distilling a centralized teacher into decentralized one-step actors under the CTDE.The Cost of Classical Multi-Agent Path Finding
Multi-Agent Path Finding (MAPF) is the problem of planning conflict-free paths for multiple agents in a shared space, each from its start to its goal.Know the Shape, Find the Fault: Topology-Conditioned Diagnosis of Multi-Agent LLM Failures
Multi-agent LLM systems coordinate task execution through exchanges of information among agents.A Society of Researchers: Designing Institutions for Populations of Autonomous Research Agents
Deployments of research agents are moving to populations of thousands that share one pool of compute, while most current systems organize one project at a time or leave the population unorganized.Decentralized SGD under Heavy-Tailed Noise: Optimal Convergence Rates and the Role of Gradient Clipping
Heavy-tailed noise has been widely observed in modern machine learning, motivating the use of methods like gradient clipping and normalization.From Investigation Failures to Reliable SOC Agents: Understanding and Improving LLM-Based Alert Triage
Security operations centers (SOCs) must triage large volumes of alerts, most of which are benign, while missed attacks can remain uninvestigated.RFChipAgent: Multi-Agentic AI Flow for Analog/RF Chip Design
Analog/RF circuits remain the critical interface between digital computation and the physical world, and emerging standards from Wi-Fi 7 to 6G place stringent demands on them, yet analog/RF design…Decentralized collaborative continual learning: A multi-objective minimization-based technique
In this work, we formulate decentralized continual learning within a multi-objective optimization framework.Reading the Room: Foundations, Design, and Challenges of Normative Competence in LLMs
Human communities are governed by normative systems: shared standards that produce \textit{norms} dictating acceptable behavior, enforced through community sanctioning.Disentangling Models from Personas in Heterogeneous LLM Simulations
Multi-agent simulations with large language models (LLMs) often operate networks of agents with a single base model.Where Rules End and Judges Begin: Measuring the Judgment Boundary in Multi-Agent Systems Security
LLM-based multi-agent systems (MAS) engage tools, share memory, and delegate tasks, often encountering adversarial content.Joint Workflow and Prompt Optimization for User Behavior Simulation
User behavior simulation is the computational modeling of user interactions within information systems through the use of simulated agents in place of live users.