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.
Get the few papers worth your time in Multiagent Systems every morning.
Follow Multiagent Systems and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 13
Scam Town: Can Scam Education Spread Like a Vaccine?
Most older adults who hear a warning about scams hear it from someone they know: a relative, a neighbour, or a friend who was targeted.Explore or Confirm? LLM Agents Misallocate Measurements Under Noise
As model reasoning gets cheaper, the physical experiment becomes the slow and costly step in discovery.How Far Can an Agent Push? Trust-Safety Margins in Live Language-Based Economic Games
Game theory identifies when a strategic action should be accepted, but not how long a live, language-based counterpart will continue to accept it.IF-MAP: Influence-Function-Inspired Agent Prioritization in Multi-Agent Systems
Improving every agent in an LLM-based multi-agent system can be prohibitively costly, making it important to identify which agent should be prioritized to achieve the greatest system-level gain with…Adding Heavy-Ball Momentum to Distributed Constrained Optimization for Energy Resource Management Subject to Time-Delays and Quantization
This paper studies a hybrid discrete-time signed gradient-consensus method with heavy-ball momentum, paired communication delays, and fixed logarithmic quantization.Low-Bit Distributed Constrained Optimization with Application to Optimal Scheduling and Allocation
This paper proposes a distributed resource allocation algorithm in which each agent communicates only the sign of its local cost gradient, a single bit per directed link per iteration.CARVS: A Congestion-Aware Algorithm for Online Multi-Agent Pickup-and-Delivery in Human-Collaborative Warehouses
Intelligent warehouse systems have transformed logistics by integrating robots with minimal infrastructure changes, boosting efficiency and optimizing workflows compared to traditional human-only…Neuro-Inspired Inhibitory Message Passing for Accurate and Token-Efficient Multi-Agent Reasoning
Multi-agent systems promise to solve problems by bringing together information beyond the reach of any individual agent.Cooperation Without Shared Rewards via Reciprocal Q-Augmentation
General-sum games are more challenging than fully cooperative or adversarial settings because agents may deceive or exploit one another.Measuring Consensus in AI Agent Networks
As AI agents become increasingly connected through networks and take on tasks that require negotiation and joint decision-making, a systematic approach is needed to assess how their views converge…AgentSoV: Virtual Sensing for LLM Multi-Agent Systems via Stream of Variation
Large language model (LLM) multi-agent systems (MASs) solve complex tasks through interacting agents, yet their reliability is difficult to analyze because failures depend on both individual agents…The One-Pixel of Reasoning: One Truthful Relation Is Enough to Mislead LLM Agents
Can one sentence manipulate an agent's belief by targeting a single implicit warrant linking evidence to a conclusion?Same Data, Different Bytes: Serialization-Invariant Integrity Checks for Agent-Published Datasets
Agent networks require reliable ways for requesting agents to verify where data is located, how it can be accessed, and whether the data received matches what the data owner made available.Cooperation Without Adaptation: LLM Agents in a Collective-Risk Dilemma
Language-model agents are increasingly deployed to act on behalf of people in settings where individual decisions shape shared outcomes.Provable Authority: A Protocol for Verifiable Authority Resolution and Control Across Human, Organizational, and Agentic Transactions
Payment systems authenticate users, devices, accounts, and cryptographic credentials, but a relying party, such as a counterparty, payment rail, marketplace, or autonomous agent runtime, generally…KiranaBench: Can a Language Model Run a Neighbourhood Shop?
Large language model (LLM) agents are increasingly evaluated on long-horizon tasks, including autonomously running a business.Thought Blocks: Non-Autoregressive Latent Communication for Multi-Agent Systems via Trajectory-to-State Compilation
LLM-based multi-agent systems typically communicate through text, incurring repeated generation and re-encoding costs.Cryptographically Secure Agent-to-Agent Communication in Multi-Agent Systems
Multi-agent systems (MAS) comprise AI agents that collaborate or compete to perform complex, distributed tasks.Towards High Semantic Fidelity: Hyperdimensional Symbolic Messages in Multi-Agent Communication
Semantic fidelity is essential for multi-agent communication under non-ideal channels, comprising transmission fidelity and conversion fidelity.Annotrace: A Workbench for Step-Level Annotation of Agent Traces
Every study of why LLM agents fail begins by labelling traces by hand, and every such study builds its own throwaway tool.