Project Description

Designing Better Games Using Artificial Intelligence, Automated Play Testing, and Computational Creativity
Aaron Isaksen (NYU Game Innovation Lab)

Making great games requires searching a massive space of all possible games to discover the hidden gems — which takes a huge amount of effort from designers and many hours of play testing. At the NYU Game Innovation Lab, we have developed methods to automate this process and assist designers in improving their games. I will show how we use artificial intelligence and player simulation to estimate the difficulty of different variants of Flappy Bird, using automated play testing to help a designer understand the effects of changing each game parameter. I also will show how we use genetic algorithms and computational creativity to find new variants of Flappy Bird that are as different from the original as possible. This talk will focus on practical methods coming from academic game labs which indie game designers can try to integrate into their own design process.



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Aaron Isaksen (NYU Game Innovation Lab)

Aaron Isaksen is a PhD Candidate at the NYU Polytechnic School of Engineering Game Innovation Lab, studying automated game tuning, player modeling using probability distributions and survival analysis, and data-driven computer-aided game design. He has been working in the games industry since 2003 (creating Chip Chain and other indie mobile games), is a founding partner of Indie Fund (which aims to support the growth of games as a medium by helping indie developers get and stay financially independent, is an Advisory Board member for Fig (a new crowdfunding platform for indie games), and is the Chairman of IndieBox (which offers a subscription service for physical collectors editions of digital independent games).