{
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  "@id": "https://anchorfact.org/kb/multi-agent-reinforcement-learning",
  "headline": "Multi-Agent Reinforcement Learning: Cooperation, Competition, and Emergent Strategies",
  "description": "Multi-Agent Reinforcement Learning (MARL) extends RL to systems where multiple agents learn simultaneously — collaborating, competing, or negotiating. From drone swarms to trading agents, MARL captures emergent collective intelligence that exceeds the sum of individual policies.",
  "dateCreated": "2026-05-24T02:49:13.638Z",
  "dateModified": "2026-05-24",
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    "name": "AnchorFact"
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  "publisher": {
    "@type": "Organization",
    "name": "AnchorFact",
    "url": "https://anchorfact.org"
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  "license": "https://creativecommons.org/licenses/by/4.0/",
  "anchorfact:confidence": "high",
  "anchorfact:generationMethod": "ai_assisted",
  "citation": [
    {
      "@type": "CreativeWork",
      "name": "A multi-agent reinforcement learning framework for exploring iterated and evolutionary games",
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      "@type": "CreativeWork",
      "name": "A Comprehensive Survey on Multi-Agent Cooperative Decision Making",
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