Estimating the strength of poker hands by integer linear programming techniques

Marcello Dalpasso () and Giuseppe Lancia ()

Central European Journal of Operations Research, 2015, vol. 23, issue 3, 625-640

Abstract: We illustrate how integer linear programming techniques can be applied to the popular game of poker Texas Hold’em in order to evaluate the strength of a hand. In particular, we give models aimed at (1) minimizing the number of features that a player should look at when estimating his winning probability (called his equity), (2) giving weights to such features so that the equity is approximated by the weighted sum of the selected features. We show that ten features or less are enough to estimate the equity of a hand with high precision. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Poker Texas Hold’em; Integer linear programming; Equity (search for similar items in EconPapers)
Date: 2015
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://hdl.handle.net/10.1007/s10100-014-0366-3 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:cejnor:v:23:y:2015:i:3:p:625-640

Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/10100

DOI: 10.1007/s10100-014-0366-3

Access Statistics for this article

Central European Journal of Operations Research is currently edited by Ulrike Leopold-Wildburger

More articles in Central European Journal of Operations Research from Springer, Slovak Society for Operations Research, Hungarian Operational Research Society, Czech Society for Operations Research, Österr. Gesellschaft für Operations Research (ÖGOR), Slovenian Society Informatika - Section for Operational Research, Croatian Operational Research Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().