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In this report, we summarize the takeaways from the first NeurIPS 2021NetHack Challenge. Participants were tasked with developing a program or agentthat can win (i.e., 'ascend' in) the popular dungeon-crawler game of NetHack byinteracting with the NetHack Learning Environment (NLE), a scalable,procedurally generated, and challenging Gym environment for reinforcementlearning (RL). The challenge showcased community-driven progress in AI withmany diverse approaches significantly beating the previously best results onNetHack. Furthermore, it served as a direct comparison between neural (e.g.,deep RL) and symbolic AI, as well as hybrid systems, demonstrating that onNetHack symbolic bots currently outperform deep RL by a large margin. Lastly,no agent got close to winning the game, illustrating NetHack's suitability as along-term benchmark for AI research.

Insights From the NeurIPS 2021 NetHack Challenge