Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently

Muthuraman Chidambaram; Yanjun Qi

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arXiv · 1702.06762

Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently

Muthuraman Chidambaram·Yanjun Qi

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Abstract

The idea of style transfer has largely only been explored in image-based tasks, which we attribute in part to the specific nature of loss functions used for style transfer. We propose a general formulation of style transfer as an extension of generative adversarial networks, by using a discriminator to regularize a generator with an otherwise separate loss function. We apply our approach to the task of learning to play chess in the style of a specific player, and present empirical evidence for the viability of our approach.

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Muthuraman Chidambaram, Yanjun Qi. 2017-02-22. Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently. https://arxiv.org/abs/1702.06762

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