Survey explores computational methods in mechanism design, revealing insights into learning and optimization techniques.
In this note, we survey automated mechanism design (AMD): the use of computational techniques to solve mechanism design problems. We describe three distinct but overlapping threads of research: an optimization-based paradigm that formulates mechanism design as linear programming, a line of work on sample complexity and learning theory, and the recent trend of differentiable economics , which has produced state-of-the-art results on a range of problems by borrowing tools and techniques from modern deep learning.
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Curry et al. (2025) studied this question.
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