---
res:
  bibo_abstract:
  - "In modern sample-driven Prophet Inequality, an adversary chooses a sequence of
    n items with values v1,v2,…,vn to be presented to a decision maker (DM). The process
    follows in two phases. In the first phase (sampling phase), some items, possibly
    selected at random, are revealed to the DM, but she can never accept them. In
    the second phase, the DM is presented with the other items in a random order and
    online fashion. For each item, she must make an irrevocable decision to either
    accept the item and stop the process or reject the item forever and proceed to
    the next item. The goal of the DM is to maximize the expected value as compared
    to a Prophet (or offline algorithm) that has access to all information. In this
    setting, the sampling phase has no cost and is not part of the optimization process.
    However, in many scenarios, the samples are obtained as part of the decision-making
    process.\r\nWe model this aspect as a two-phase Prophet Inequality where an adversary
    chooses a sequence of 2n items with values v1,v2,…,v2n and the items are randomly
    ordered. Finally, there are two phases of the Prophet Inequality problem with
    the first n-items and the rest of the items, respectively. We show that some basic
    algorithms achieve a ratio of at most 0.450. We present an algorithm that achieves
    a ratio of at least 0.495. Finally, we show that for every algorithm the ratio
    it can achieve is at most 0.502. Hence our algorithm is near-optimal.@eng"
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Krishnendu
      foaf_name: Chatterjee, Krishnendu
      foaf_surname: Chatterjee
      foaf_workInfoHomepage: http://www.librecat.org/personId=2E5DCA20-F248-11E8-B48F-1D18A9856A87
    orcid: 0000-0002-4561-241X
  - foaf_Person:
      foaf_givenName: Mona
      foaf_name: Mohammadi, Mona
      foaf_surname: Mohammadi
      foaf_workInfoHomepage: http://www.librecat.org/personId=4363614d-b686-11ed-a7d5-ac9e4a24bc2e
  - foaf_Person:
      foaf_givenName: Raimundo J
      foaf_name: Saona Urmeneta, Raimundo J
      foaf_surname: Saona Urmeneta
      foaf_workInfoHomepage: http://www.librecat.org/personId=BD1DF4C4-D767-11E9-B658-BC13E6697425
    orcid: 0000-0001-5103-038X
  bibo_doi: 10.48550/ARXIV.2209.14368
  dct_date: 2022^xs_gYear
  dct_language: eng
  dct_title: Repeated prophet inequality with near-optimal bounds@
...