cs.MA · 2026-05-27 · No. 10

Multiagent Systems, 2026-05-27.

2 new papers in cs.MA. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

2 entries
  1. 01

    Cost of Structural Learning Under Censored Feedback: A Threshold-Bandit Approach

    Michael Ledford, William Regli

    cs.MA · cs.LG

    In many multi-agent applications, tasks yield rewards only when executed by a coalition meeting an unknown size threshold; otherwise, feedback is fully censored. This censorship creates an identifiability problem: agents cannot distinguish stochastic failure from insufficient coordination. We formalize this setting as the Threshold-Activated Cooperative Multi-Armed Bandit (TAC-MAB) and analyze it under both centralized and decentralized...

    arxiv.org/abs/2605.27076 · PDF

  2. 02

    Persistent AI Agents in Academic Research: A Single-Investigator Implementation Case Study

    Anas H. Alzahrani

    cs.MA · cs.AI · cs.HC

    Background: Large language models are typically evaluated as models, benchmarks, or short conversational episodes. Less is known about what happens when an agent is embedded persistently in a real academic research environment with durable memory, local files, external tools, scheduled routines, delegated roles, and explicit safety protocols. Methods: A structured self-observed implementation case study was conducted from January 31 to May...

    arxiv.org/abs/2605.26870 · PDF

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