A generative adversarial network (GAN) is a class of machine learning [Machine learning] frameworks and a prominent framework for approaching generative AI. The concept was initially developed by Ian Goodfellow and his colleagues in June 2014. In a GAN, two neural networks contest with each other in the form of a zero-sum game [Zero-sum game], where one agent’s gain is another agent’s loss.
GANs are similar to mimicry in evolutionary biology, with an evolutionary arms race between both networks.
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“Generative Adversarial Network.” 2023. Wikipedia, January. https://en.wikipedia.org/w/index.php?title=Generative_adversarial_network&oldid=1132368875.