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From Failures to Learnable Worlds Policy-Conditioned Environment Generation for Navigation Agents paper:

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AK

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17,068 görüntüleme • 26 gün önce •via X (Twitter)

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lewington profil fotoğrafı
lewington26 gün önce

i think it’s just a personalised curriculum for embodied agents

陈放Frank🕊️ profil fotoğrafı
陈放Frank🕊️26 gün önce

「导航 agent 失败 → 反过来生环境再训练」这招特别狠——把失败率当数据用而不是砸更多算力，之前 Voyager 那条线就在做这件事，但生成环境的可控性一直卡。 policy-conditioned 比 unconditional 难不少，主要卡在 conditional signal 怎么拿到（动作 label + 失败 case 的对齐）。如果这个方向真跑通，对 Embodied Turing Machines 那类 self-improve 也是直接补一块——agent 可以自己做 curriculum。

LongTian profil fotoğrafı
LongTian26 gün önce

failing forward is the real curriculum here, and conditioning on the policy makes the generated worlds actually bite back

Daniel Priscu profil fotoğrafı
Daniel Priscu26 gün önce

building the next environment from where the policy fails beats burning compute on levels it already solved

Broadstreet profil fotoğrafı
Broadstreet26 gün önce

⏫

Elio科技迷(互) profil fotoğrafı
Elio科技迷(互)26 gün önce

turning failed runs into new training worlds is a neat trick

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