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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Newest papers, page 5
Distributed Grid Search for Hyperparameter Tuning
The performance of many distributed optimization algorithms over peer-to-peer networks strongly depends on the choice of their hyperparameters.ORION: An Outcome-Driven LLM Advisor for RL-Based Multi-Domain 6G Slice Placement
Deploying 6G network slices across administrative domains requires an online decision for each arriving request: which domain hosts each virtual network function, how traffic crosses domain…AI evaluators favor job applications written by certain AI models, independent of candidate quality
Job applicants increasingly use large language models (LLMs) to write cover letters, while employers deploy LLMs to screen them.Adaptive Coverage Algorithms for Mobile Ad Hoc Networks in Dynamic Worlds
This paper extends an existing framework for the coordination of mobile agents in unknown worlds, by considering the possibility of dynamic instability.Strategic Tanking in Stable Matching Markets
Motivated by a broad literature in psychology, organizational behavior, and matching markets, we introduce strategic tanking: an agent deliberately makes themselves less attractive to selected…Decentralized Multi-Agent Coordination and Communication in Shared Codebases
Coding agents working in shared repositories may receive separate, independently-motivated requests from human developers, creating a setting that is multi-agent by necessity.PCM: A Proof-Carrying Message Protocol for Verifiable Multi-Agent Communication
When one AI agent tells another that "the tests passed" or "a person approved this refund", the receiver has only the sender's word.Soei: Structured Observability of Evidence and Intent for Multi-Agent AI Software Engineering
AI coding agents now do long, multi-step and multi-session software work with little supervision.Bayesian Offline Multi-Agent Reinforcement Learning with Latent World Models
Model-based offline multi-agent reinforcement learning (MARL) provides a promising approach to multi-agent decision-making under partial observability, where the global state is unavailable from…Sticky Collusion: Persistence of LLM Agent Collusion after Incentive Removal and Partner Replacement
We ask whether collusion between AI agents survives once formed, when its incentive is removed or a colluder is replaced.Can AI Agents Interface Clinicians and Complex Models?
Contemporary healthcare institutions generate daily very large amounts of data, which contain highly useful information for the improvement of work organization, planning and overall efficiency.Long-Term Agent Memory through Complementary Curation and Consolidation
Long-horizon dialogue agents require effective memory systems to recall facts, events, and relationships from interaction histories.Learning Calibrated Confidence for Multi-Agent Collaboration
Complex information seeking on the Web often requires collecting evidence from multiple documents and reasoning across them, as in multi-hop question answering.EpiAgent: Epistemic Self-Play for LLM Agents
Epistemic game theory explains an agent's strategic behavior via the beliefs it holds about others and how these beliefs are updated as the interactions unfold.MAServeBench: Benchmarking Multi-Agent LLM Serving Systems with Hierarchical Collaboration Workloads
Large language model (LLM)-based multi-agent systems (MAS) coordinate specialized agents to solve complex tasks, turning each user request into interdependent model and tool operations.Collaborative AI agents for autonomous experimental research with solid-state quantum spins
An autonomous research laboratory could conduct an entire study, from formulating questions to preparing manuscripts.How a group that cannot communicate knows itself by its enemy
Teams that cannot communicate seem stuck with what each member sees.Agentic World Modeling for Agent Test-time Scaling without Environment Replica
Test-time scaling (TTS) improves large language model agents by sampling and selecting among multiple candidate trajectories, but common realizations assume that these trajectories can be executed…Renegotiable Options Fail to Prevent Hold-Up Between Two Profit-Maximizing Frontier LLM Agents
Do contract terms that protect investment between people also protect it between profit-maximizing language-model agents?A Robust Approach to Belief Mismatch in Non-cooperative Dynamic Games
Game-theoretic models are increasingly used to describe multi-agent interactions in control and robotics applications.