{
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  "@type": "article",
  "@id": "https://anchorfact.org/kb/deep-reinforcement-learning-algorithms",
  "headline": "Deep Reinforcement Learning Algorithms: PPO, SAC, Dreamer, and Decision Transformer",
  "description": "Deep Reinforcement Learning has evolved from simple DQN to sophisticated algorithms: PPO dominates continuous control, SAC excels at sample-efficient exploration, Dreamer learns world models, and Decision Transformer reframes RL as sequence modeling.",
  "dateCreated": "2026-05-24T02:49:13.599Z",
  "dateModified": "2026-05-24",
  "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": "ai_assisted",
  "citation": [
    {
      "@type": "CreativeWork",
      "name": "Proximal Policy Optimization Algorithms (PPO)",
      "sameAs": "https://arxiv.org/abs/1707.06347"
    },
    {
      "@type": "CreativeWork",
      "name": "Mastering Diverse Domains through World Models (Dreamer v3)",
      "sameAs": "https://arxiv.org/abs/2301.04104"
    }
  ]
}