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Thursday, April 27, 2017 - 3:15pm to 4:00pm

Using Artificial Intelligence to Test the Candy Crush Saga Game

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Candy Crush Saga is one of the biggest mobile games today with more than 1000 levels of difficulty—and users continue to ask for more. When building new content, it is extremely important to ensure that the level of difficulty is balanced and that the user does not experience crashes or problems through some unforeseen level of play. Stefan Freyr shows you how King is training artificial intelligence (AI) programs (bots) to test its games by mimicking human interactions. Join Stefan as he discusses how King is taking testing to the next level by employing Monte Carlo Tree Search, automatic heuristic construction, and NeuroEvolution of Augmenting Topologies (NEAT) to train bots to test and evaluate difficulty levels. He discusses ways to extend and use AI bots to predict game success rates and conduct automatic performance testing. Stefan explains how this AI approach can be generalized to test other applications. Learn how AI can help you with testing that's getting very difficult to master with traditional testing techniques.

 

Alexander_Andelkovic
King/Midasplayer AB

Alexander Andelkovic is the agile testing lead for Sweden-based King/Midasplayer AB, developer of the popular mobile game Candy Crush Saga, Alexander Andelkovic has worked on multiple complex test projects ranging from using session-based test management for quality assuring MED-Tech devices for life critical systems to establishing a world class approval process for Spotify apps used by Fortune 500 companies. Now he teams with developers in testing big data, business analytics, and game level regression testing using AI. Alex performs both system testing and exploratory testing with a focus on assisting teams with high-quality deliveries. He is a frequent speaker at international conferences including both STAREAST and STARWEST.