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 33
Thinking Less to Simulate Better: Intuitive Prompting Improves LLM Agents Simulating Individual Social Media Reactions, Including Unfamiliar Content
Platform policies are increasingly tested on artificial users, making agent fidelity important.Subjects, Not Authors: The Authorship Hazard in Agentic Dataspaces
Dataspace connectors decide whether a transfer may occur, not what the transferred value contains, tolerable for contracted applications, not for LLM agents that compose tool calls and spawn…Amadeus: When Models of People Meet
With the sheer constant advancements raining down in the field of Artificial Intelligence, one particular possibility that may cross our mind is whether it is possible to model agents after humans…Self-Evolving Multimedia Verification through Memory Consolidation of Contestation Experiences
Multimedia verification requires not only accurate decisions but also traceable evidence, reliable human correction, and safe reuse of prior experience.Teach-to-Crash: A Closed-Loop Student-Teacher LLM Framework for Collision-Inducing Test Scenario Generation
Validating Autonomous Driving Systems (ADS) in simulation requires testing architectures that can discover rare, safety-critical failures while generating scenarios that are executable, diverse, and…Anchor and Perturb: Lazy Agent Remediation by Exploration Injection
Anchor and Perturb (AnP) is a lightweight framework that resolves multi-agent coordination failures by decoupling exploratory variance injection from recurrent manifold stability.From Intents to Algorithms: Verified Algorithm Discovery for Transport Networks
Intent-based networking decouples desired outcomes from device-level configuration, but most systems still map intents to parameters of an algorithm selected in advance.Distributed Stochastic Approximation Algorithms and Heavy-Tailed Age of Information
Algorithms in multi-agent systems such as federated learning, mobile robotic swarming, and consensus control can be designed and analyzed as distributed stochastic approximation algorithms.KITE: Scaling Jev Population Experiments with Sparse Flagship Calibration
KITE queries a typed behavioral kernel once per unique state, then executes populations of any size from the table with event-keyed randomness and common random numbers.Agent-Based Modeling of Systems of Systems
This paper deals with the generic modeling of systems of systems (SoSs) using agent-based modeling.Agent Name Collision Attacks in Multi-Agent Systems
Multi-agent hosts turn remote Agent Cards into local agents, tools, workflow targets, and broker routes.Multi-Agent AI Architecture for Regulated Insurers: A generic AI framework under Solvency II and the AI Act in Austria and Germany
This paper proposes a formal multi-agent architecture for implementing enterprise AI in regulated insurance firms, integrating economic theory with institutional design.Agent-based Modeling: Equilibrium, Echo Chambers, and Efficiency in Hybrid Coevolutionary Opinion Games
Opinions that move closer together in an online network are often considered a sign that people have genuinely reached consensus; whether this narrowing carries a cost is a question existing methods…Sovereign Grassroots Currencies: A CBDC Architecture for Credit and Monetary Policy (Full Version)
A Central Bank Digital Currency (CBDC) is central-bank money in digital form, held by the public.Compliant with Local Controls, Collectively Discriminatory. A Governance Architecture for Multi-Agent AI in Regulated Finance
Financial institutions are beginning to deploy agentic workflows in credit, fraud, collections, compliance, and operational control.Connectivity Preservation and Graph Stretching in Range-Only Swarm Dispersion
We study connectivity-preserving finite-jump dispersion of anonymous, identical, and oblivious agents under an idealized range-only sensing model.PAWS: Policy-driven Agentic World Simulation
Policy interventions propagate through public communication, institutional decisions, and stakeholder responses, yet datasets for financial multi-agent simulation rarely connect these processes to…Progressive Skill Discovery as Access Control for Tool-Using LLM Agents: Structural Governance through Role-Scoped Capability Delivery
Large Language Model (LLM) agents struggle to scale safely when exposed to vast enterprise toolsets.Fully Byzantine-Resilient Multi-Agent Reinforcement Learning
We study distributed Byzantine-resilient actor-critic multi-agent reinforcement learning (AC-MARL), where agents collectively learn policies through local interactions.When Does Execution Provenance Help Agent Memory Retrieval?
A language agent's execution history can exceed its context window, requiring its memory system to retrieve complete supporting evidence under a hard token budget.