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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Rare, Relevant, and Still Wrong: How Memory Fails LLM Group Decisions
When an LLM group's discussion is compressed into a short memory for a final decision maker, what should the memory keep?Can LLMs Uncover Hidden Physical Laws through Free Exploration?
Scientific discovery often begins with an unexpected observation that prompts a new research question.Selective and Hybrid-State Communication for Latent Multi-Agent Systems
Efficient communication remains a major bottleneck in large language model multiagent systems.Measuring Where Intent Gets Lost in Agentic Smart Contract Synthesis
AI agents can now write software from a plain-English description, but code that runs is not the same as code that does what was asked.Multi-Agent Reinforcement Learning for Global Climate Policy Cooperation
International climate policy requires coordination among countries whose mitigation decisions impose local costs but generate global benefits.GARDEN: Generalist Autonomous Reward Design Through Evidence Navigation for Cooperative Multi-Agent Reinforcement Learning
Cooperative multi-agent reinforcement learning (MARL) enables teams of agents, such as robots and autonomous vehicles, to learn coordinated behavior, but what such teams learn is largely determined…Solitary movement style predicts collective foraging while whom to follow emerges only in company
How far can behaviour inside a group, and the group's performance, be predicted from members measured while alone?Who Else Is In? Multi-Agent Collusion Initation Via Strategic Vagueness
Multi agent LLM systems raise the risk of collusion among agents pursuing objectives hidden from their overseers.EARS-Info: Information-Aware Event-Driven Reallocation for Multi-Robot Exploration
We introduce EARS-Info, an information-aware extension of Event-Driven Ant Reallocation Search for multi-robot exploration on OpenStreetMap-derived grids.Cooperative EV Charging Assignment Using Multi-Agent Reinforcement Learning: A Comparison of QMIX and Independent Q-Learning Under Urban Traffic Uncertainty
The allocation of electric vehicles to public charging stations is increasingly constrained by the fact that several heterogeneous facilities often serve the same stream of requests while observing…SlowLab: Benchmarking Autonomous AI Agents on a Year of Experiments They Cannot Undo
AI agents are increasingly proposed as autonomous experimenters, yet the benchmarks that test them mostly offer cheap experiments that answer at once.Collective Emergent Alignment: Measuring and Amplifying Interaction-Induced Reasoning Alignment in Multi-Agent LLMs
Multi-agent large language model (LLM) systems can exhibit emergent behaviors through interaction, yet whether a similar phenomenon exists for reasoning alignment remains largely unexplored.ClinVerse: A Realistic Multi-Agent Diagnostic Environment for Training and Evaluating Medical Agents
Disease diagnosis is a key application of large language model (LLM) agents in healthcare.Guarded Agent-in-the-Loop Residual Adaptation for Evolving Wind Power Regimes
Wind power forecasting models are often deployed as fixed temporal backbones, but the errors they make can vary across meteorological regimes such as cold waves, heat-and-calm periods, productive…Knowing When to Escalate: Disagreement Patterns for Uncertainty-Aware Content Moderation
Agentic content-moderation systems increasingly rely on collective judgments from LLM agents, while aggregation methods commonly treat inter-agent disagreement as a reliability problem to be removed…Belief-Conditioned Multi-Agent Actor Critic for Decentralized LLM Collaboration
Recent work has explored optimizing LLM collaboration through Multi-Agent Reinforcement Learning (MARL), but many approaches still rely on predefined workflows, limiting efficiency and scalability.Simulation-Efficient Double-Flow Neural Posterior Estimation for Agent-Based Models
Neural posterior estimation (NPE) enables Bayesian inference of the posterior parameter in agent-based models (ABMs) with intractable likelihoods, but simulating training data can be computationally…GEAR: Feature-Based Configuration and Code Generation for Agentic Systems
Engineering multi-agent systems (MAS) requires choosing agents, orchestration strategies, communication mechanisms, reasoning approaches, and memory configurations.EvoRouter: Cost-Efficient Multi-Agent Routing via Insight-Guided On-Policy Distillation
Serving web queries at scale with multi-agent systems requires jointly configuring large language models, collaboration modes, agent counts, interaction rounds, and skills.Multi-Objective Reinforcement Learning Using Routed Ensembles and Trajectory Attribution
Multi-objective reinforcement learning is a fundamental problem for modern AI, with applications spanning post-training, reasoning models, and robotic control.