{
  "id": "2005.12126",
  "title": "Learning to Simulate Dynamic Environments with GameGAN",
  "authors": "Seung Wook Kim, Yuhao Zhou, Jonah Philion, Antonio Torralba, Sanja Fidler",
  "first_public": "2020-05-25",
  "first_public_source": "https://arxiv.org/abs/2005.12126",
  "venue": "CVPR 2020",
  "arxiv": "2005.12126",
  "paper_url": "https://arxiv.org/abs/2005.12126",
  "lens": [
    "interactive-worlds"
  ],
  "related_terms": [
    "GameGAN",
    "neural game engine",
    "interactive simulation",
    "visual memory"
  ],
  "summary": "Learns an interactive visual game simulator from gameplay and keyboard actions using a generative adversarial network.",
  "contribution": "Introduces a memory module for revisited locations and separates static and dynamic image components, enabling visual consistency and component recombination.",
  "limitations": "The simulator learns from recorded games, with memory organized as a spatial map.",
  "model_output": "The next game-screen image.",
  "action_interface": "Game controls represented by keyboard actions.",
  "state_memory": "Recurrent dynamics plus an external memory module that stores an internal environmental map.",
  "relationship": "An earlier interactive neural simulator discussed in NeuralOS's related work.",
  "relationship_source": "https://arxiv.org/html/2507.08800v2",
  "author_names": [
    "Seung Wook Kim",
    "Yuhao Zhou",
    "Jonah Philion",
    "Antonio Torralba",
    "Sanja Fidler"
  ],
  "record_url": "https://neural-os.com/reading-list/papers/2005.12126/",
  "legacy_record_url": "https://neural-os.com/reading-list/papers/#paper-2005-12126",
  "citation_date": "2020-05-25",
  "json_url": "https://neural-os.com/reading-list/papers/2005.12126/record.json",
  "markdown_url": "https://neural-os.com/reading-list/papers/2005.12126/index.md",
  "bibtex_url": "https://neural-os.com/reading-list/papers/2005.12126/citation.bib",
  "csl_url": "https://neural-os.com/reading-list/papers/2005.12126/citation.csl.json"
}