{
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  "@type": "TechArticle",
  "@id": "https://anchorfact.org/kb/kb-2026-00272",
  "headline": "Reinforcement Learning",
  "description": "Reinforcement Learning (RL) trains agents to make sequential decisions by maximizing cumulative reward through trial-and-error interaction with an environment. Key concepts: Agent, Environment, State, Action, Reward, Policy. Famous successes: AlphaGo, Dota 2 (OpenAI Five), robotics.",
  "dateCreated": "2026-05-22T14:59:47.502Z",
  "dateModified": "2026-05-22T14:59:47.502Z",
  "author": {
    "@type": "Organization",
    "name": "AnchorFact"
  },
  "publisher": {
    "@type": "Organization",
    "name": "AnchorFact",
    "url": "https://anchorfact.org"
  },
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "anchorfact:confidence": "high",
  "anchorfact:generationMethod": "human_only",
  "citation": []
}