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Intro

What is matchmaking?

What is Machine Learning?

Machine Learning and Matchmaking

State of the Art Today: Skill

Real-time matchmaking

First Configure a Set of Rules

Example Configuration

Matchmaker Receives Requests

Matchmaker Request

Compares Requests

Creates a Match

Rules Apply Globally

Predictability How often the better team wins

Conventional Takeaway

More Optimal Approach

Defining Optimal

High-level Comparison

Unified objective function

As an Equation

Utility Function Use

True Match algorithm

True Match components

Population tracker

Population model

Metric Predictor

Simplest wait time formula • matchable(t) = requests that can match with t

Parameterized wait time formula

Optimizer: How does it make Rules?

Start with Current Rules

Find Optimal Transform Need to rewrite to search all curves

We found it!

True Match Rule Example Scale = 10, remember gap of 1 is OK

Mapped vs. Conventional

True Match Rules

What about Regions?

Conventional Region Approach

True Match Approach

FFA example

Skill gap variation

Wait time variation

True Match FFA Take-away

True Match Takeaway

Simple Improvements Matchmake on scaled Skill Percentiles

Thank you! Questions?

Description:

Explore TrueMatch, a revolutionary matchmaking approach presented by 343 Industries' Josh Menke in this 2020 GDC Virtual Talk. Discover how machine learning can be leveraged to automatically optimize desired metrics in real-time, allowing developers to express the value of each metric more intuitively. Delve into the intricacies of matchmaking, machine learning, and their intersection in game development. Learn about the current state of skill-based matchmaking and real-time techniques. Understand the limitations of conventional approaches and how TrueMatch offers a more optimal solution through unified objective functions and utility functions. Examine the components of the TrueMatch algorithm, including population trackers, metric predictors, and optimizers. Gain insights into handling regional matchmaking and free-for-all scenarios. Compare conventional and TrueMatch approaches through practical examples and visualizations. Conclude with simple improvements and key takeaways to enhance your game's matchmaking system. Read more

Machine Learning for Optimal Matchmaking

GDC

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#Conference Talks #GDC (Game Developers Conference) #Programming #Game Development #Computer Science #Machine Learning #Real-Time Systems #Algorithms #Algorithm Optimization

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