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      "statement": "# Overcooked human-aware collaborative learning testbed\n\nIntroduces a simplified cooperative game testbed and compares self-play/population-based agents with agents trained or planned using behavior-cloned human models, including real-human collaboration tests.\n\n## Scientific scope\n\nHuman-model benefits depend on model fit and task layout; the planning experiment's benefit requires access to the exact proxy model and real-human results are weaker. This is a generic coordination benchmark, not a food/agricultural achievement, universal human cooperation solution or invention of behavior cloning.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nMicah Carroll; Rohin Shah; Mark K. Ho; Thomas L. Griffiths; Sanjit A. Seshia; Pieter Abbeel; Anca Dragan\n\nSource-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.\n\n\n\n## Original sources\n\n- [On the Utility of Learning about Humans for Human-AI Coordination](https://arxiv.org/pdf/1910.05789v1)\n",
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