A Unifying Hierarchy of Valuations with Complements and Substitutes

Abstract

We introduce a new hierarchy over monotone set functions, that we refer to as MPH (Maximum over Positive Hypergraphs). Levels of the hierarchy correspond to the degree of complementarity in a given function. The highest level of the hierarchy, MPH-m (where m is the total number of items) captures all monotone functions. The lowest level, MPH-1, captures all monotone submodular functions, and more generally, the class of functions known as XOS. Every monotone function that has a positive hypergraph representation of rank k (in the sense defined by Abraham, Babaioff, Dughmi and Roughgarden [EC 2012]) is in MPH-k. Every monotone function that has supermodular degree k (in the sense defined by Feige and Izsak [ITCS 2013]) is in MPH-(k+1). In both cases, the converse direction does not hold, even in an approximate sense. We present additional results that demonstrate the expressiveness power of MPH-k.One can obtain good approximation ratios for some natural optimization problems, provided that functions are required to lie in low levels of the MPH hierarchy. We present two such applications. One shows that the maximum welfare problem can be approximated within a ratio of k+1 if all players hold valuation functions in MPH-k. The other is an upper bound of 2k on the price of anarchy of simultaneous first price auctions.

Cite

Text

Feige et al. "A Unifying Hierarchy of Valuations with Complements and Substitutes." AAAI Conference on Artificial Intelligence, 2015. doi:10.1609/AAAI.V29I1.9314

Markdown

[Feige et al. "A Unifying Hierarchy of Valuations with Complements and Substitutes." AAAI Conference on Artificial Intelligence, 2015.](https://mlanthology.org/aaai/2015/feige2015aaai-unifying/) doi:10.1609/AAAI.V29I1.9314

BibTeX

@inproceedings{feige2015aaai-unifying,
  title     = {{A Unifying Hierarchy of Valuations with Complements and Substitutes}},
  author    = {Feige, Uriel and Feldman, Michal and Immorlica, Nicole and Izsak, Rani and Lucier, Brendan and Syrgkanis, Vasilis},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2015},
  pages     = {872-878},
  doi       = {10.1609/AAAI.V29I1.9314},
  url       = {https://mlanthology.org/aaai/2015/feige2015aaai-unifying/}
}