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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When AI Advisors Agree: Distinguishing Forecast Risk from Forecast Reliability
If seven AI advisors agree, what have we learned: that their forecast is reliable, or that the asset is easier to forecast?Collective Autonomous Vehicle Routing Needs Social Awareness for Coexistence with Human Drivers
Collective Autonomous Vehicle (AV) route choices in real-world traffic networks can create externalities for Human-Driven Vehicles (HDVs), as routes that benefit AVs may increase travel times for…Limit-sure Winning in Team Games without Shared Randomness
We study concurrent stochastic games in which a team of agents plays against an adversarial environment.A Multi-Agent LLM System for Automated Tuning of Specialized Neural Network Models
Many machine learning approaches are two-level: an expert selects a class of methods, within this class the choice of key components is critical and usually manual.Cooperative Aerial Transportation of a Payload with a Sliding Cable Attachment
This paper presents a dual-quadrotor hook- suspended transport system for cooperative aerial manipulation of a payload that is not rigidly attached to a fixed point along the cable.OpenSocialJax: Evaluating Social Adaptation in Sequential Social Dilemmas with Open-Ended Environmental Dynamics
Sequential social dilemma benchmarks capture diverse social interactions, but rarely test whether agents can infer hidden environmental rules through repeated interaction while adapting to other…MARGoS: A Configuration-Driven Platform for Reproducible MARL Experiments in ARGoS
Multi-agent reinforcement learning (MARL) has become a prominent research direction, particularly within collective robotics, where the ARGoS simulator is widely used to study emergent swarm behavior.Ask Your Advisor: Learning When to Consult Stronger Models in Agentic Systems
To balance task performance and computational cost, agentic workflows can use a lower-cost model for execution and selectively consult a stronger model.Akule: Fast and Scalable Multi-Robot Motion Planning via Sparse Interaction Diffusion
Diffusion models provide expressive trajectory priors for multi-robot motion planning (MRMP), but scaling them to large teams requires coordinating individual motions without expensive joint…ANASSA: From High-Level Framework to Low-Level Architecture for Spatial Agentic AI
Agentic AI systems operating over geospatial data require more than autonomous reasoning and tool use; they must also support explicit orchestration, spatial validation, governance, provenance…Personalization Matters: Long-Horizon Conversation Agent with User-Centric Information in Online Shopping Interactions
Personalized conversational shopping requires maintaining preference consistency over multi-turn interactions, where users reveal constraints gradually.An Embodied Multiagent Framework Based on Token Communications for Cooperative ISAC
The emerging low-altitude economy demands unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC) for reliable connectivity and environmental awareness.SWE-Journey: Towards More Realistic Evaluation of Coding Assistants through Long-Horizon, Multi-Turn Interaction
Coding assistants such as Claude Code and Codex have become a major application of LLM agents, yet existing benchmarks remain far from real-world use, particularly in task horizon and interaction…Epistemic Disturbance in the Graph Model for Conflict Resolution: State-Preserving Actions, Four-Valued Assessments, and the Distinction between Capability and Intention
In the graph model for conflict resolution (GMCR), a decision maker (DM) either moves the conflict to another state or does nothing.ConventionPlay: Capability-Limited Training for Robust Ad-Hoc Collaboration
Ad-hoc collaboration often requires agents to identify and adhere to some shared convention within a cooperative task.MindFlow: Mind Supernet Powered Thinking Flows for Research Idea Innovation
Research idea innovation is a fundamental engine of scientific progress, yet it remains difficult to generate and evaluate in a scalable and controllable way.Policy Synthesis for Finite Populations of MDP Agents under Aggregate Reach-Avoid Chance Constraints
Consider a finite population of agents with decoupled Markov transition dynamics and empirical-density feedback, subject to the following constraints: with probability at least $1-δ_r$, at least a…OA-MAP: Evidence-Grounded Multi-Agent Multimodal Framework for Interpretable Knee Osteoarthritis Progression
Knee osteoarthritis (KOA) progression prediction can support patient monitoring, requiring the integration of multimodal data and multidomain expertise.Spatial Pattern Formation from Multi-Agent Learning in Public Goods Dilemmas
Spatial public goods models show that prescribed movement toward richer locations can generate spatial patterns.Ecology of AI Agents: Collaboration Creates a Population Threshold for Takeoff
AI agents can now conduct real-world cyberattacks, scale up capabilities with the number of agents, and collectively pursue misaligned goals to obtain rewards.