Scaling Laws for Pre-training Agents and World Models
Scaling Laws for Pre-training Agents and World Models
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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The performance of embodied agents has been shown to improve by increasing model parameters, dataset size, and compute. This has been demonstrated in domains from robotics to video games, when generative learning objectives on offline datasets (pre-training) are used to model an agent's behavior (imitation learning) or their environment (world mode...
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Scaling Laws for Pre-training Agents and World Models
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TN_cdi_proquest_journals_3126159841
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3126159841
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E-ISSN
2331-8422
