Artificial Intelligence (AI) in Testing: The Future Is Now

When building new content for a game such as Candy Crush Saga that has more than 1000 levels, it is extremely important to make sure that the level of difficulty is balanced and that the user does not experience crashes or problems through some unforeseen type of play. Alexander Andelkovic shows you how King is training AI-programs (bots) to test its games by mimicking human interactions. Alex explains 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. Alex shares how this AI approach can be generalized to test other applications. Learn how AI can help you with testing that's getting too difficult to accomplish with traditional testing techniques.