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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Organizational Learning in Materials Discovery Campaigns: Which Databases, Calculations, and Agent Teams Pay Off
More databases can make a materials campaign worse.Coati: Host-Grounded Execution for Installable Mobile GUI Agents
Mobile GUI agents can carry out tasks across apps, yet most run on a separate computer that drives a phone over the Android Debug Bridge (ADB), out of reach of ordinary users and of the apps through…Source-Resolved Collective Cognition in Robotics: Mathematical Foundations for Multimodal and Collective Estimation, and Their Reach across the Cognition Loop
The Generalized Singular Value Decomposition (GSVD) is a central tool for comparing two linear operators that act on the same unknown.Multi-Modal Multi-Agent System for Bridge Operation and Maintenance based on Large Language Model
Bridges are critical transportation infrastructure, and reliable operation and maintenance (O&M) is essential for traffic safety and long-term structural performance.SelfImprove-Bench: Evaluating Generalization in Self-Improving Agents
Recursively self-improving (RSI) systems are increasingly viewed as a promising means of accelerating progress toward artificial general intelligence.AGiR: Mitigating Gift Over-Reliance in Mixed-Motive Games
In this paper, we consider mixed-motive games (MMGs) which model various real-world multi-agent scenarios where self-interested agents must both cooperate and compete.Cloudra: Geometric Reasoning and Scientific Validation for Autonomous Reaction Mechanism Exploration
Autonomous reaction-mechanism exploration requires proposing reaction steps, preparing three-dimensional structures, and determining which reactant and product a computed saddle point connects.Classification Aggregation with Multiple Memberships
People face the problem of classifying objects into categories while aggregating their opinions.The Tower of Babel in artificial intelligence: who should speak, and when it pays to listen
Two machines can each recognize an object well and still fail together.KlaskTron: An Open-Source Platform for Physical Adversarial Multi-Agent RL
Progress in robot learning, particularly physical multi-agent reinforcement learning (MARL), is currently challenged by a limited availability of accessible, standardized benchmarks.An Axiomatic Framework for Reinforcement Learning in Open Multi-Agent Systems
Open multi-agent systems, where only a subset of agents are controllable, are central to real-world domains such as smart grids, yet lack a principled foundation for reinforcement learning algorithm…Optimize the Harness, Not the Model: Fitting a Minimal Agent to a Self-Hostable LLM for Investigative Analysis
Government intelligence teams need LLM agents that can analyze large, messy evidence collections, but security and cost constraints often rule out hosted frontier models and broad, hard-to-audit…VIAS: Value-Isolating Activation Steering for Multi-Value Alignment and Compliance for Organisations
Organisations increasingly deploy large language model agents that must follow organisational values.FedReady: Bounded Agents for Federation Formation
Federated learning (FL) runtimes standardize aggregation and deployment, but each new study still requires federation formation: selecting task-eligible sites and preparing their local data and task…Four Bridges: Measuring Deception Propensity in a Multi-Agent Game
AI agents are increasingly deployed in settings where they interact and coordinate with other agents, yet honesty is mostly measured in single-turn, single-agent benchmarks that pressure the model…El Agente Fármaco: A Scalable AI Scientist for Drug Discovery
Computational drug discovery offers a growing range of tools for proposing and evaluating molecules, but combining them and deciding what to do next still requires substantial expert effort.Beyond Division of Labor: How Roles Shape Feedback and Recovery in Multi-Agent Systems
Roles in multi-agent large language model (LLM) systems allocate decisions as well as work.Labtune: Treating Lab Organization and Information Sharing as Experimental Variables in LLM-Agent Discovery
De-siloing can create groupthink; silos can prevent knowledge sharing and reduce research efficiency.A Guideline-Grounded Multi-Agent Framework for Personalized Exercise Prescription from Clinical and Wearable Data
Translating population-level exercise guidance into individualized prescriptions requires integrating clinical and wearable data, including diagnoses, medications, functional limitations, and…Finite-Sample Convergence in Networked Average Reward MARL: Decentralization Pitfalls and Entropy Remedies
We study the problem of average reward Multi-Agent Reinforcement Learning (MARL) where agents interact within a network.