An AI Approach to VLT Games Modeling

Video Lottery Terminals (VLT) are common gaming machines for money usually found in various venues. These machines are anonymous and stateless and do not record any information about player’s identity. The data obtained from these machines is very complex and hard to analyse. The gaming industry is keen to understand how a game or a possible change to a game will be perceived in different environments by different types of customers. This understanding will provide insights into both gaming performance and responsible gaming related behaviours. The most common current approach is to release a game, monitor the data and the analyze the results along with player interviews. This is expensive and inefficient, and many players choose to abstain from participating in these experiments. One goal in this project is to identify the most relevant VLT data features to predict positive user experiences and train models that imitate the behaviour of players to get a good estimation of a machine learning model as a reliable substitute for real world players. TO BE CONT’.

Faculty Supervisor:

Vlado Keselj;Colin Conrad

Student:

Partner:

IGT

Discipline:

Computer science

Sector:

Arts, entertainment and recreation; Information and cultural industries

University:

Dalhousie University

Program: