"reinforcement learning" meaning in English

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      "expansion": "reinforcement learning (uncountable)",
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  "lang": "English",
  "lang_code": "en",
  "pos": "noun",
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          "kind": "other",
          "name": "English entries with incorrect language header",
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          "source": "w"
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        {
          "kind": "topical",
          "langcode": "en",
          "name": "Artificial intelligence",
          "orig": "en:Artificial intelligence",
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      "derived": [
        {
          "english": "deep reinforcement learning",
          "word": "DRL"
        },
        {
          "english": "reinforcement learning from AI feedback",
          "word": "RLAIF"
        },
        {
          "english": "reinforcement learning from human feedback",
          "word": "RLHF"
        }
      ],
      "examples": [
        {
          "ref": "2010, Lutz Frommberger, Qualitative Spatial Abstraction in Reinforcement Learning, Springer Science & Business Media, page 10",
          "text": "Reinforcement learning can be seen as somewhere between supervised and unsupervised learning. The learning system receives a feedback for its actions, but it is not provided with examples to learn from.",
          "type": "quotation"
        },
        {
          "ref": "2022, Aske Plaat, Deep Reinforcement Learning, Springer Nature, page 3",
          "text": "Let us look more deeply at reinforcement learning, to see what it means to learn from our own actions. Reinforcement learning is a field in which an agent learns by interacting with an environment.",
          "type": "quotation"
        }
      ],
      "glosses": [
        "A type of explorative learning via feedback in a simulated environment."
      ],
      "id": "en-reinforcement_learning-en-noun-x1TA1RRS",
      "links": [
        [
          "machine learning",
          "machine learning"
        ],
        [
          "explorative",
          "explorative"
        ],
        [
          "learning",
          "learning"
        ],
        [
          "feedback",
          "feedback"
        ],
        [
          "environment",
          "environment"
        ]
      ],
      "qualifier": "machine learning",
      "raw_glosses": [
        "(machine learning) A type of explorative learning via feedback in a simulated environment."
      ],
      "synonyms": [
        {
          "word": "RL"
        }
      ],
      "tags": [
        "uncountable"
      ],
      "translations": [
        {
          "code": "fi",
          "lang": "Finnish",
          "sense": "Translations",
          "word": "vahvistusoppiminen"
        },
        {
          "code": "fr",
          "lang": "French",
          "sense": "Translations",
          "tags": [
            "masculine"
          ],
          "word": "apprentissage par renforcement"
        },
        {
          "code": "de",
          "lang": "German",
          "sense": "Translations",
          "tags": [
            "neuter"
          ],
          "word": "bestärkendes Lernen"
        }
      ]
    }
  ],
  "word": "reinforcement learning"
}

{
  "derived": [
    {
      "english": "deep reinforcement learning",
      "word": "DRL"
    },
    {
      "english": "reinforcement learning from AI feedback",
      "word": "RLAIF"
    },
    {
      "english": "reinforcement learning from human feedback",
      "word": "RLHF"
    }
  ],
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      "expansion": "reinforcement learning (uncountable)",
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  "lang": "English",
  "lang_code": "en",
  "pos": "noun",
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        "en:Artificial intelligence"
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      "examples": [
        {
          "ref": "2010, Lutz Frommberger, Qualitative Spatial Abstraction in Reinforcement Learning, Springer Science & Business Media, page 10",
          "text": "Reinforcement learning can be seen as somewhere between supervised and unsupervised learning. The learning system receives a feedback for its actions, but it is not provided with examples to learn from.",
          "type": "quotation"
        },
        {
          "ref": "2022, Aske Plaat, Deep Reinforcement Learning, Springer Nature, page 3",
          "text": "Let us look more deeply at reinforcement learning, to see what it means to learn from our own actions. Reinforcement learning is a field in which an agent learns by interacting with an environment.",
          "type": "quotation"
        }
      ],
      "glosses": [
        "A type of explorative learning via feedback in a simulated environment."
      ],
      "links": [
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          "machine learning",
          "machine learning"
        ],
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          "explorative",
          "explorative"
        ],
        [
          "learning",
          "learning"
        ],
        [
          "feedback",
          "feedback"
        ],
        [
          "environment",
          "environment"
        ]
      ],
      "qualifier": "machine learning",
      "raw_glosses": [
        "(machine learning) A type of explorative learning via feedback in a simulated environment."
      ],
      "synonyms": [
        {
          "word": "RL"
        }
      ],
      "tags": [
        "uncountable"
      ]
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  ],
  "translations": [
    {
      "code": "fi",
      "lang": "Finnish",
      "sense": "Translations",
      "word": "vahvistusoppiminen"
    },
    {
      "code": "fr",
      "lang": "French",
      "sense": "Translations",
      "tags": [
        "masculine"
      ],
      "word": "apprentissage par renforcement"
    },
    {
      "code": "de",
      "lang": "German",
      "sense": "Translations",
      "tags": [
        "neuter"
      ],
      "word": "bestärkendes Lernen"
    }
  ],
  "word": "reinforcement learning"
}