AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The findings suggest that human-motivated theories of simplicity can inform the design of decision environments for artificial agents and show why scaffolds should be evaluated through realized choices as well as explanations: improvements in one need not appear in the other.
Surprisingly, without task-specific fine-tuning or calibration to human bids, the three non-reasoning large models robustly preserve key orderings of auction formats by deviation from theory.
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