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Symmetry-Breaking Augmentations for Ad Hoc Teamwork
Feb. 16, 2024, 5:42 a.m. | Ravi Hammond, Dustin Craggs, Mingyu Guo, Jakob Foerster, Ian Reid
cs.LG updates on arXiv.org arxiv.org
Abstract: In many collaborative settings, artificial intelligence (AI) agents must be able to adapt to new teammates that use unknown or previously unobserved strategies. While often simple for humans, this can be challenging for AI agents. For example, if an AI agent learns to drive alongside others (a training set) that only drive on one side of the road, it may struggle to adapt this experience to coordinate with drivers on the opposite side, even if …
abstract adapt agent agents ai agents artificial artificial intelligence arxiv breaking collaborative cs.ai cs.lg drive example humans intelligence set simple strategies symmetry teamwork training type
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