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.
- Finite gambling problem
- Geometric convergence
ASJC Scopus subject areas
- Computer Science Applications
- Management Science and Operations Research