Achieving COSMOS: a metric for determining when to give up and when to reach for the stars

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Tosch:2012:GECCOcomp,
  author =       "Emma Tosch and Lee Spector",
  title =        "Achieving COSMOS: a metric for determining when to
                 give up and when to reach for the stars",
  booktitle =    "1st workshop on Understanding Problems (GECCO-UP)",
  year =         "2012",
  editor =       "Kent McClymont and Ed Keedwell",
  isbn13 =       "978-1-4503-1178-6",
  keywords =     "genetic algorithms, genetic programming",
  pages =        "417--424",
  month =        "7-11 " # jul,
  organisation = "SIGEVO",
  address =      "Philadelphia, Pennsylvania, USA",
  DOI =          "doi:10.1145/2330784.2330848",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "The utility of current metrics used in genetic
                 programming (GP) systems, such as computational effort
                 and mean-best-fitness, varies depending upon the
                 problem and the resource that needs to be optimized.
                 Inferences about the underlying system can only be made
                 when a sufficient number of runs are performed to
                 estimate the relevant metric within some confidence
                 interval. This paper proposes a new algorithm for
                 determining the minimum number of independent runs
                 needed to make inferences about a GP system. As such,
                 we view our algorithm as a meta-metric that should be
                 satisfied before any inferences about a system are
                 made. We call this metric COSMOS, as it estimates the
                 number of independent runs needed to achieve the
                 Convergence Of Sample Means Of the Order Statistics. It
                 is agnostic to the underlying GP system and can be used
                 to evaluate extant performance metrics, as well as
                 problem difficulty. We suggest ways for which COSMOS
                 may be used to identify problems for which GP may be
                 uniquely qualified to solve.",
  notes =        "Also known as \cite{2330848} Distributed at
                 GECCO-2012.

                 ACM Order Number 910122.",
}

Genetic Programming entries for Emma Tosch Lee Spector

Citations