{
  "abstract": "Multi-agent systems are commonly improved by adding agents, increasing communication, or strengthening individual capabilities. However, more agents and more communication do not always produce better collective intelligence. Agents may provide redundant information, interfere with one another's reasoning, reinforce incorrect conclusions, or consume resources without contributing sufficient value. This paper proposes a general framework for investigating whether suppressing selected forms of intelligence within a multi-agent system can enhance other forms of intelligence or improve collective performance.\n\nThe framework considers suppression at several levels, including individual agents, agent capabilities, communication links, messages, decision-making influence, and collaborative behaviors. Suppression may be temporary, partial, adaptive, or reversible. Its objective is not simply to reduce the size of a system, but to determine whether reducing a particular contribution allows other agents or processes to perform more effectively. A mathematical formulation is introduced to distinguish agent-level enhancement, interaction-level enhancement, and system-level improvement. Potential mechanisms include interference reduction, resource reallocation, reduced information redundancy, improved specialization, and changes in decision-making influence. The paper also proposes an experimental design for evaluating selective suppression against appropriate baselines. The framework does not assume that suppression is always beneficial. Instead, it establishes a general research direction for identifying what should be suppressed, what should be enhanced, and under what conditions suppression improves collective intelligence.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "name": "Jincheng Zhang",
      "orcid": "0009-0005-1860-0009"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ds3rzb1nhhwaa.bib",
  "cited_by": 0,
  "doi": "10.5281/zenodo.23469197",
  "fulltext_url": null,
  "id": "ds3rzb1nhhwaa",
  "issns": [],
  "landing_url": "https://zenodo.org/records/23469197",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [],
  "openalex": null,
  "pdf_url": "https://zenodo.org/api/records/23469197/files/Enhancing%20Intelligence%20Through%20the%20Suppression%20of%20Other%20Intelligence%20A%20General%20Framework%20for%20Multi-Agent%20Systems.pdf/content",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-19",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/ds3rzb1nhhwaa.ris",
  "sources": [
    {
      "first_seen": "2026-11-02T12:21:12Z",
      "native_id": "23469197",
      "source": "zenodo",
      "url": "https://zenodo.org/records/23469197"
    }
  ],
  "subjects": [],
  "title": "Enhancing Intelligence Through the Suppression of Other Intelligence: A General Framework for Multi-Agent Systems",
  "title_text": "Enhancing Intelligence Through the Suppression of Other Intelligence: A General Framework for Multi-Agent Systems",
  "type": "preprint",
  "updated_at": "2026-11-02T12:21:12Z",
  "url": "https://research.draconitic.com/paper/ds3rzb1nhhwaa",
  "venue": "Zenodo",
  "versions": []
}