Artificial Intelligence and Optimization in the Casino Industry

Session Title

Session 1-1-D: Data and Player Behavior

Presenters

Anastasia (Stasi) D. Baran, nQube Data Science Inc.Follow

Presentation Type

Event

Location

Caesars Palace, Las Vegas, Nevada

Start Date

28-5-2019 9:15 AM

End Date

28-5-2019 10:40 AM

Disciplines

Artificial Intelligence and Robotics | Business Analytics | Business Intelligence | Gaming and Casino Operations Management | Numerical Analysis and Scientific Computing | Other Business | Technology and Innovation

Abstract

Artificial intelligence (AI) is becoming more prevalent in the casino industry. It allows casinos to both improve customer experience and improve their bottom line. AI has the ability to automate processes, make better decisions about customer preferences, and find efficiencies that are not discoverable by human observers. We present a powerful, AI-driven, multi-objective evolutionary optimization and data modelling platform, called Qubist. The Qubist platform, along with underlying, “plug-in” mathematical models, is used in several casino applications such as slot floor optimization, AI-driven segmentation of slot machines and player databases, and most recently, sportsbook automation and strategy optimization. We present an overview of the models behind each of the applications, and compare them to standard practices in the casino industry. Moreover, we explore what true mathematical optimization means from a scientist’s perspective, compared to how optimization is interpreted by traditional vendors and casino operators. We present results from anonymized data sources, derived from player tracking systems.

Keywords

Artificial Intelligence, Optimization, Data Science, Analytics, Slot Floor, Sportsbook

Author Bios

Anastasia (Stasi) Baran is a Co-founder and COO of nQube Data Science Inc. She received her PhD in Electrical and Computer Engineering from the University of Manitoba in 2016, where she specialized in applications of non-linear optimization methods. She holds a B.Sc. in physics and an M.Sc. in astrophysics. Stasi uses her multi-disciplinary background and computing expertise to find and develop suitable applications for nQube’s advanced artificial intelligence-driven optimization suite.

Funding Sources

This research is privately funded by nQube Data Science Inc. The author is COO of nQube. The topics addressed align with our business interests.

Competing Interests

None.