Revolutionizing Casino Floors: Machine Learning Boosts Slot Machine Maintenance & Revenue

Introduction

The world of casino gaming is continually evolving, with companies constantly searching for ways to improve the player experience and maximize revenue. A groundbreaking partnership between Light & Wonder, a prominent casino gaming technology company, and Amazon ML Solutions Lab promises to revolutionize the gaming industry further. The collaboration’s primary objective is to develop a machine learning (ML) powered predictive maintenance system for slot machines, reducing downtime and enhancing the gaming experience for players.

Problem Formulation

The central ML challenge faced in this partnership comprises predicting possible machine failures or breakdowns in electronic gaming machines. Accurate and timely predictions of machine malfunctions would enable more efficient maintenance schedules, leading to reduced downtime. To achieve this, companies first must define appropriate evaluation metrics to gauge the performance of the ML models. The effectiveness of these models has significant implications for the gaming experience and, ultimately, casino revenue.

Data Preparation

The critical first step in tackling this challenge is acquiring relevant data. Light & Wonder gathers invaluable machine performance data through LnW Connect, their proprietary data management system. However, data acquisition and preparation come with a set of challenges, such as data gathering from numerous machine models and data formats. These obstacles necessitate extensive data preprocessing and feature engineering to transform raw data into structured, ML-friendly information.

Data Preprocessing and Feature Engineering

Feature engineering plays a crucial role in refining raw data into valuable features that enhance the model’s performance. Data preprocessing ensures that ML models can efficiently process the data by converting it into appropriate formats and eliminating noise. These two processes provide essential building blocks for machine learning models to function optimally.

Model Selection and Training

Two neural network architectures have been identified during the project’s development: Convolutional Neural Networks (CNN) and Transformers. Both architectures are capable of analyzing complex patterns in the data. However, it was decided to implement a combined CNN+Transformer model as it held the potential to capitalize on the strengths of both architectures.

Hyperparameter Tuning

Hyperparameter tuning is crucial in refining the performance of machine learning models. In this project, Amazon SageMaker’s Automatic Model Tuning streamlines the process and assists in determining the ideal configurations for the selected model. This further improves model performance and accuracy in predicting machine failures.

Model Comparison

Comparing the baseline model performance against the final CNN+Transformer model highlights the significant performance improvements brought by the chosen ensemble model. Enhanced predictive maintenance through machine learning subsequently reduces downtime, increases player satisfaction, and ultimately generates increased revenue for casinos.

Advanced Techniques for Model Improvement

In addition to the CNN+Transformer model, ensembling was introduced as an advanced technique for model enhancement. By leveraging the predictions from multiple models, ensembling can provide more accurate predictions, further boosting game machine uptime. Other techniques, such as anomaly detection and reinforcement learning, also hold promise in tackling the challenges faced in the gaming industry.

The collaboration between Light & Wonder and Amazon ML Solutions Lab has led to impressive achievements in the realm of predictive maintenance for electronic gaming machines. Implementing the ML-powered system has a profound impact on improving the gaming experience for casino patrons, while simultaneously increasing casino revenue. This collaboration paves the way for exploring further opportunities for cutting-edge machine learning solutions in the gaming industry and beyond.