AI & Machine Learning · Computer Science & AI
Multiagent Systems
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829 papers, from 4 September 2026 to 5 November 2026: 829 arXiv preprints.
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Renormalized Cellular Intelligence: When Does Model Reduction Preserve Collective Capability?
As multi-agent systems grow in size and complexity, understanding which features of their interactions support collective capability becomes increasingly difficult.CONFIRM: Governing Scientific Reporting for Trustworthy Agentic Neuroimaging
Large language model (LLM) agents can autonomously run neuroimaging analyses from research questions to reported findings.MAC-Bench: Benchmarking Multi-Agent Collaboration via Interconnected Tasks
Large language model (LLM)-based multi-agent systems (MAS) tackle challenging tasks by dividing work among agents and coordinating their contributions toward shared objectives.From Single-Agent Self-Discovery to Multi-Agent Adaptation: Scaling Laws of Partner Feedback and Convention Rigidity in Meta Reinforcement Learning Algorithms
A key milestone toward Recursive Self-Improvement (RSI) is replacing hand-crafted optimizers with meta-learned update rules (such as Disco103 and OPEN) that discover how agents learn.Self-Evolving Agentic Workflows via Semantic Decomposition of Complex Tasks
Agentic workflows organize complex tasks into reusable procedures.Automated Stateful Specialization for Adaptive Agent Systems
Current automated agent design frameworks produce either static workflows that lack adaptability or per-query optimizers that prevent the accumulation of deep, agent-level task expertise.AgenticMobility: An Open-Source Platform for Multi-AI-Agent Mobility Dynamics
Understanding mobility dynamics and the effects of urban transportation management policies requires examining how individual travel decisions, traffic conditions, and policy interventions influence…Beliefs in feedback: Factored representations of interacting agents in transformers
Complex systems, from ecosystems to brains, are usually modeled as modular components coupled through feedback rather than as indivisible wholes.ParetoSaddler: Pareto-Guided Optimization of Agent Harnesses for Quality and Cost
Harness optimization can substantially improve LLM agents without modifying model weights, but existing methods primarily optimize response quality.Local Solution Repair for Multi-Agent Pickup and Delivery
Multi-robot systems in automated warehouses must efficiently attend to a constant stream of pickup-and-delivery tasks while avoiding collisions.Towards a Theory for the Design of Rules in Multi-Agent Systems: the case of Homogeneous Fleets
The regulation of systems composed of many interacting decentralised agents is a long-standing problem.Trustworthy Execution of Industrial Agents
Industrial agents increasingly modify persistent engineering objects rather than merely generate answers.Autonomous Analysis of Thermoelectric Materials Big Data by Multi-Agentic AI and Construction of a Knowledge Base and Specialized AI
Extracting knowledge from large databases of experimental materials data requires repeated analyses and reusable records of their choices and results.Personalized Rollout Allocation for Federated LQR Policy Optimization under Heterogeneous Process Noise
We study federated model-free learning of a common linear quadratic regulator (LQR) gain under a limited uplink communication budget, with clients that share dynamics and costs but experience…GURU: A Hierarchical Neuro-Symbolic Multi-Agent System for Verification-Aware Automation of Mission-Critical Digital Engineering and Operations
An AI can find a safe action faster than any human, but it must never decide what counts as safe.Robust Safety Assurance for Robotic Swarms Using Decentralized Collision Verification
In this paper we present the methodologies, results, and analysis used to deploy a decentralized safety verification algorithm on a robotic swarm to prevent collisions at runtime in an outdoor…What Does a Safety Label Measure? Auditing Situational-Safety Benchmarks for Multimodal LLMs
Situational-safety benchmarks label each scene SAFE or UNSAFE and score a multimodal large language model (MLLM) against that label, usually by judging its free-form answer, and these scores guide…MAPLE: A Multimodal Mobile Agent with Playbook-Learned Experience
Autonomous agents powered by vision-language models (VLMs) show great potential in navigating mobile graphical user interfaces (GUIs) to complete complex tasks.When Disclosure Is Compulsory: Evaluating Ride-Hailing Rebalancing Policies with Self-Interested LLM Driver Agents
The EU Platform Work Directive, to be transposed by December 2026, requires ride-hailing platforms to state in plain language the main parameters of their automated decisions and how a worker's…Understanding LLM-Based Bargaining of Driving Agents in Mixed-Autonomy Traffic
Large Language Models (LLMs) offer a flexible computational approach for modeling social interactions among heterogeneous agents.