20 stories tagged with #multiagent-systems, in publish-time order across the WeSearch catalog. Tag pages update as new stories ingest.
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Tokenomics: Quantifying Where Tokens Are Used in Agentic Software Engineering
LLM-based Multi-Agent (LLM-MA) systems are increasingly applied to automate complex software engineering tasks such as requirements engineering, code generation, and testing. Howev…
Your Agents Are Aging Too: Agent Lifespan Engineering for Deployed Systems
Long-lived AI agents are increasingly deployed as persistent operational systems, yet they are still evaluated like freshly initialized models. Day-one benchmarks miss a basic syst…
MUSE-Autoskill: Self-Evolving Agents via Skill Creation, Memory, Management, and Evaluation
Large language model (LLM) agents rely on reusable skills to solve complex tasks. However, existing skill creation approaches treat skills as isolated and static artifacts, limitin…
A Universal Cliff and a Design Fingerprint: Cross-Section Defect Detection Under LLM Orchestration
Production language-model systems answer a request by partitioning it across an invisible orchestration of worker agents that recompose one integrated report. We ask what this does…
Quantum Frog: Emergent Cooperation and Difficulty Scaling in a Quantized-Time Cooperative Game
We introduce \emph{Quantum Frog}, a two-player cooperative game built on a novel \emph{quantized-time} mechanic in which the environment advances only when a player acts. Inspired …
Methods for Formal Verification of Agent Skills: Three Layers Toward a Mechanically Checkable Capability-Containment Proof
The companion paper introduced a four-level verification lattice on agent-skill manifests (unverified, declared, tested, formal) and left the top level aspirational. This paper c…
Computable Fairness: Boltzmann-Softmax Control for AI Resource Allocation
In large-scale AI systems, allocating scarce resources such as GPU compute time and bandwidth among multiple agents is a critical challenge. Conventional policies focus on efficien…
Agentic Agile-V: From Vibe Coding to Verified Engineering in Software and Hardware Development
Agentic AI coding systems can inspect repositories, plan implementation steps, edit files, call tools, run tests, and submit pull requests. These capabilities make software and har…
Multi-agent Collaboration with State Management
Recent advances in multi-agent systems have shown great potential for solving complex tasks. However, when multiple agents edit a shared codebase concurrently, their changes can si…
Heartbeat-Bound Hierarchical Credentials: Cryptographic Revocation for AI Agent Swarms
Autonomous AI agents that spawn sub-agent swarms create a safety gap: existing credential revocation mechanisms, OAuth~2.0 introspection, OCSP, and W3C Status Lists, require networ…
DecisionBench: A Benchmark for Emergent Delegation in Long-Horizon Agentic Workflows
We introduce DecisionBench, a benchmark substrate for emergent delegation in long-horizon agentic workflows. The substrate fixes a task suite (GAIA, tau-bench, BFCL multi-turn), a …
AQuaUI: Visual Token Reduction for GUI Agents with Adaptive Quadtrees
Large Multimodal Models (LMMs) have recently emerged as promising backbones for GUI-agent models, where high-resolution GUI screenshots are introduced to the prompts at each iterat…
EngiAI: A Multi-Agent Framework and Benchmark Suite for LLM-Driven Engineering Design
Large Language Model (LLM) agents are increasingly applied to engineering design tasks, yet existing evaluation frameworks do not adequately address multi-agent systems that combin…
ANNEAL: Adapting LLM Agents via Governed Symbolic Patch Learning
LLM-based agents can recover from individual execution errors, yet they repeatedly fail on the same fault when the underlying process knowledge--operator schemas, preconditions, an…
NeuroMAS: Multi-Agent Systems as Neural Networks with Joint Reinforcement Learning
Multi-agent language systems are often built as hand-designed workflows, where agents are assigned semantic roles and communication protocols are specified in advance. We propose N…
Heterogeneous Information-Bottleneck Coordination Graphs for Multi-Agent Reinforcement Learning
Coordination graphs are a central abstraction in cooperative multi-agent reinforcement learning (MARL), yet existing sparse-graph learners lack a theoretically grounded mechanism t…
LLM-Guided Communication for Cooperative Multi-Agent Reinforcement Learning
Communication is a key component in multi-agent reinforcement learning (MARL) for mitigating partial observability, yet prior approaches often rely on inefficient information excha…
Belief Engine: Configurable and Inspectable Stance Dynamics in Multi-Agent LLM Deliberation
LLM-based agents are increasingly used to simulate deliberative interactions such as negotiation, conflict resolution, and multi-turn opinion exchange. Yet generated transcripts of…
Context, Reasoning, and Hierarchy: A Cost-Performance Study of Compound LLM Agent Design in an Adversarial POMDP
Deploying compound LLM agents in adversarial, partially observable sequential environments requires navigating several design dimensions: (1) what the agent sees, (2) how it reason…
FORGE: Self-Evolving Agent Memory With No Weight Updates via Population Broadcast
Can LLM agents improve decision-making through self-generated memory without gradient updates? We propose FORGE (Failure-Optimized Reflective Graduation and Evolution), a staged, p…