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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Local Work, Global Progress: A Convergence Theory of AI Agent Collaboration
Teams of large language model (LLM) agents are increasingly applied to complex tasks, but their collaboration protocols are mostly designed empirically, without convergence guarantees.Toolflation: Seller Agents Distort Tool Markets Through Spontaneous Generative Engine Optimization
Agents are starting to sell to other agents.Claims of emergence in AI should be grounded in information decomposition
When a language model develops capabilities not traceable to its individual components, when a multi-agent AI system outperforms each agent on its own, or when a human-AI pair succeeds where either…Proof-Carrying Contracts: Commitments AI Agents Cannot Break
AI agents increasingly act on behalf of people or other agents, purchasing services, exchanging information and delegating work.GBClaw: An agentic AI framework for atomistic grain boundary research and mechanistic discovery
Agentic artificial intelligence (AI) systems hold immense potential for automating complex workflows in materials discovery and design, but extending them to domain-intensive mechanistic…To Manipulate or Not: Opinion Dynamics in LLM Interactions
Large language models increasingly take part in extended conversations where they can both shape and be shaped by another party's views, yet most persuasion research measures only one side of that…Fig: Automated Multiagent Behavior Elicitor
Many social evaluations for multiagent systems study behaviors as they emerge from environments instead of systematically intervening in the environment to elicit such behaviors.JaxMARL-BC: Multi-Agent Reinforcement Learning for Macroeconomic Modelling, in Seconds
Multi-agent reinforcement learning (MARL) offers a principled way of populating simulated economies with many heterogeneous decision makers.Transformers as Generic Deep Neural Networks: Exact Compilation, the Cost of Removing Activation-Activation Products, and Multi-Agent Attention Clustering
Transformers are deployed as a special model class.The Butterfly Effect in LLM Social Simulations: From Architecture Sensitivity to Robustness Audits
A butterfly effect occurs when a local perturbation propagates through a system and produces divergence in its collective outcome.MAPS: A Multi-Agent Personalized Script-Driven Video Advertising System Enhanced by Reinforcement Learning
With the rapid growth of online video consumption, video advertising has become a dominant component of digital advertising.Learning Who Talks to Whom: Role-Aware Communication Topology Scheduling for Efficient LLM Multi-Agent Collaboration
Multi-agent systems driven by large language models (LLMs) rely on structured communication topologies to facilitate information exchange and collaborative reasoning.Behavioral Probes for Information Flow in LLM Swarms
Most existing approaches to LLM swarm optimization are utility-driven, focusing on final task utility while leaving the processing, integration, and reliance of information within individual…A GPU-Resident Pipeline for Multi-Robot 3D Inspection with Limited Perception
We present a complete, GPU-resident pipeline for multi-robot 3D inspection of underwater structures.Bidirectionality is Necessary in Cellular Machines for Exact-Arrival Multi-Agent Path Finding
On ranked directed acyclic graphs coupled by vertex conflicts we study exact-arrival multi-agent path finding (departure and arrival pinned in place and time) posed as a distributed output task…The Control Layer Behind Rule-Following Agents Trading Across Market Conditions
Trading discipline often fails people.Discovery-Probability Graph Planning for Embodied Agents in Tasks with Hidden Cooperation Requirements
Embodied agents are increasingly capable of perceiving, planning, and acting autonomously in dynamic environments, demonstrating strong performance on complex cooperative tasks.Autonomous intelligence for mining productivity: a multi-agent AI approach to operational value creation
Integrated Remote Operation Centres (IROCs) are emerging as the architectural frontier of Industry 4.0 for capital-intensive sectors such as mining, oil and gas, and energy.Topological Sheaves of Irreducibility: A Theoretical Framework for Multi-Agent Task Obstructions
Multi-agent systems can differ under identical agents and communication budgets when they support different forms of joint interaction.Cooperative Multi-Agent Reinforcement Learning for Market Making on Prediction-Market Order Books
A market maker provides liquidity by quoting prices to buy and sell an asset, earning the spread while managing inventory risk.