{
  "id": 189,
  "url": "https://arxiv.org/abs/2607.05352v2",
  "title": "Multiplayer Interactive World Models with Representation Autoencoders",
  "summary": "We introduce the first multiplayer world model for highly dynamic environments governed by complex physical interactions. Whereas single-player world models treat the other agents as part of the environment, ours conditions on the action streams of multiple agents, learning to attribute changes in the scene to the correct player and to stay coherent under arbitrary combinations of their actions. We study this problem in the game of Rocket League, where players compete and cooperate under fast, t",
  "authors": "Anthony Hu, Václav Volhejn, Adrien Ramanana Rahary, Chris Mulder, Aditya Makkar, Alyx Liao et al.",
  "category": "research",
  "topics": "agents-autonomy,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-06T17:31:52.000Z",
  "fetched_at": "2026-07-14T14:14:19.971Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/189",
  "original_url": "https://arxiv.org/abs/2607.05352v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}