Geometric convergence of algorithms in gambling theory

S. Ramakrishnan; W. Sudderth

doi:10.1287/moor.23.3.568

Geometric convergence of algorithms in gambling theory

S. Ramakrishnan, W. Sudderth

Mathematics

Research output: Contribution to journal › Article › peer-review

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 language	English (US)
Pages (from-to)	568-575
Number of pages	8
Journal	Mathematics of Operations Research
Volume	23
Issue number	3
DOIs	https://doi.org/10.1287/moor.23.3.568
State	Published - 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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10.1287/moor.23.3.568

Cite this

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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.",

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KW - Geometric convergence

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Geometric convergence of algorithms in gambling theory

Abstract

Keywords

ASJC Scopus subject areas

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