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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On the possibilities and limitations of LLM-based multi-agent systems for multi-criteria decision-making in healthcare operations management
Multi-criteria models for healthcare operations need weights that express how stakeholders trade off patient waiting time, provider workload, and operating cost, but these weights are difficult to…CocoRNA: Collective RNA Design with Cooperative Multi-agent Reinforcement Learning
Designing RNA sequences that reliably fold into specific secondary structures is essential for understanding their biological functions but remains a challenging computational problem.Self-Building Labs
Self-driving laboratories (SDLs) accelerate scientific discovery by automating experimental execution and optimization.LLM Evolution in a Simple Simulated Market
Arguments that AI systems will evolve in harmful ways are largely made in the abstract.Red-Teaming Multi-Agent Attacks for Loss-of-Control Risks
AI agents are growing more capable and persistent, and are being deployed in ever larger numbers.Alliance of Stochastic Routing and Reinforcement Fusion for Multi-Model Reasoning
This paper studies dynamic model routing under uncertainty in multimodal settings, where a system must select and potentially compose multiple models to answer a query.Coopshift: Post-Training Amplifies The Memory Curse In LLM Cooperation
How does post-training change cooperation during repeated interaction?The Weight of Teamwork: Does Communication Structure Help LLM Scientists Search for Scientific Laws?
Team performance is often reported as one delivered score, even though that score is produced in two stages: a system generates candidate answers and a selection rule returns one of them.Preservation and loss of algorithmic structure in experimental diffusion of joint-action norms
Everyday norms of social interaction - e.g. norms of sharing space, taking turns, or queuing - are essential to large societies, offering structured procedures for common interactions.Model Capacity Frontier: A Development Framework for LLM-Supported Social Simulation
Large language model (LLM) agents are increasingly incorporated into agent-based models (ABMs) on the premise that richer, context-sensitive human behavior can improve empirical fidelity.ROAR: Benchmarking LMM Agents under Real-Time Constraints in Multiplayer Action-Shooter Games
Large multimodal models (LMMs) are increasingly deployed as agents that perceive, reason, and act in interactive multi-agent environments.SCARCE: Emergent Institutions in Long-Horizon Multi-Agent Coding Systems
As autonomous agents become widely deployed, coordinating access to shared computing resources and services will become increasingly important.Recursive Reward Improvement via Adversarial Meta-Prompt Evolution
Recursive Self-Improvement (RSI) has gained wide attention for its ability to work with limited data.Athanor: An Agent-Native System for Autonomous Post-Training Research
Recursive self-improvement, in which AI systems build stronger AI systems, is one promising route to superintelligence.A Jury, Not an Electorate: Label-Free Reliability Estimation for Ensembles of Language Models
An ensemble of language models is a jury, not an electorate.SSR: Structural Signal Retriever for Scalable Agent Discovery in LLM-Orchestrated Multi-Agent Systems
Large-scale multi-agent ecosystems require mechanisms for discovering suitable agents without exposing entire registries to a large language model (LLM) orchestrator.A Responsibility-Centered Coordination Mechanism for Decentralized Multi-Agent Systems
Centralized orchestration provides comprehensive multi-agent coordination but creates bottlenecks in scalability, adaptability, and collective performance.Diviner: Agentic RCA with Human-Governed Adaptation for Large-Scale Infrastructure
Root-cause analysis (RCA) in large-scale distributed systems is challenging because a single symptom can cross service, data, configuration, compute, and organizational boundaries.Bias Control and Injection for Multi-Agent Aggregation
Multi-agent reasoning with large language models (LLMs) raises a central question for collective decision-making: when agents disagree, whose decision should be trusted?Agent Status Protocol (ASP): A Lightweight Specification for State Reporting in Multi-Agent Systems
The Agent Status Protocol (ASP) defines a lightweight way for heterogeneous AI agents to report their operational state to a status server, and for observers such as dashboards to receive that state…