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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El Agente Quntur: Agentic Active-Space Selection for CASSCF
Multireference calculations require time-consuming expert decisions about active spaces, state identity, and convergence.Is it my preference? Role Grounding Attack against Agent's Memory via Social Interaction
LLM-based agents now share experiences on social platforms and remember new preferences to enhance their performance.Disparity Laundering: Consensus Without Fairness in Clinical Multi-Agent Systems
Clinical large language models are increasingly fielded as multi-agent teams, on the assumption that deliberation averages out individual error.Agent Transfer Protocol: Server-Mediated Agent-to-Agent Communication Architecture for the Agentic Web
The Agentic Web needs to support continuous collaboration among agents from different organizations.Cinematize from Unreal: Agentic Choreography for Controllable World Simulation
Controllable world simulation requires more than visually plausible frames: scenes must retain persistent state, coordinated actions, and editable temporal structure.From Grind to Grasp
Discussions of complexity, knowledge and intelligence often overlook the work involved.Routed Continual Learning
Agents deployed at scale repeatedly encounter related problems, and it is natural to let them learn from each other's experience rather than starting over each time.MAS-Loop: Beyond One-Shot Orchestration towards Self-Evolving Multi-Agent Systems
Training-time multi-agent system (MAS) design seeks to learn reusable orchestration policies, yet prevailing approaches remain largely one-shot: an Orchestrator generates a system but only observes…Tunable Spatial Task Allocation with Application to Maritime Swarms
In this chapter, we explore how a team of autonomous agents can flexibly reconfigure the distribution of its members across many spatially embedded tasks using a task allocation strategy grounded in…GarmentSegAgent: Autonomous Garment Segmentation for Web Fashion Images via Textual Self-Refinement
Web fashion images support applications such as visual product search and consumer-to-shop matching, yet their visual heterogeneity makes reliable garment segmentation challenging.Remembering Is Not Enough: Refining Memories and Learning When to Use Them in Multi-Agent Systems
Memory helps LLM-based multi-agent systems reuse experience, but stored advice can be flawed or applied in the wrong situation.Feedback autocratic strategies in stochastic games
A stochastic game is an optimal control problem for multiple agents in a stochastic environment.A Simulation Testbed for Self-Governing Human-Machine Institutions
AI agents no longer act alone: they cooperate, coordinate and compete within and between groups, increasingly alongside humans who are in, on or out of ``the loop''.Evaluating Priority Dispatch for Premium Membership in On-demand Taxi-sharing
In this paper, we analyze the dispatch-level feasibility of introducing premium membership into an on-demand taxi-sharing service using a sequential optimal insertion method.Aligning Institutional Power and Operational Ability
To be socially sustainable, Agentic AI systems require normative designs that align responsibilities with the ability to fulfil them.Agent-Conditioned Routing: Diverse Reasoning Paths Within One Frozen Model
Generating several solutions can expose alternative methods, but additional trajectories often paraphrase one dominant approach.Test-Time Communication in Trading Agent Swarms
Communication between agents has mostly been studied on tasks with a shared objective and fast, clear feedback.Concordat: Typed Sessions for LLM Agents
Agents built on large language models are increasingly allowed to take consequential actions: cancelling bookings, issuing refunds, changing accounts.Strategyproof Deep Reinforcement Learning for Online Resource Allocation
Online resource allocation faces two coupled challenges: (1) allocating scarce resources efficiently under uncertain future demand, and (2) ensuring that agents report task valuations and…TANDEM: Balancing Centralized and Decentralized Critics to Address the Information Gap in Complex Multi-Agent Environments
Cooperative multi-agent reinforcement learning under centralized training with decentralized execution (CTDE) shapes decentralized policies with a centralized critic that observes the global state…