Geometric convergence of algorithms in gambling theory

S. Ramakrishnan, W. Sudderth

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

In the Dubins and Savage theory of gambling, backward induction provides an algorithm for calculating the optimal return when the gambling problem is leavable. A relatively new algorithm works for nonleavable problems. We show that these algorithms converge geometrically fast for finite gambling problems. Our argument also provides a much simpler proof of convergence for the nonleavable case.

Original languageEnglish (US)
Pages (from-to)568-575
Number of pages8
JournalMathematics of Operations Research
Volume23
Issue number3
DOIs
StatePublished - Jan 1 1998

Keywords

  • Algorithm
  • Finite gambling problem
  • Geometric convergence

ASJC Scopus subject areas

  • Mathematics(all)
  • Computer Science Applications
  • Management Science and Operations Research

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