Abstract
The game of Go is a traditional board game originated in ancient China and has long been viewed as the most challenging of board games for artificial intelligence. In 2016, AlphaGo defeated a human professional player in 19 × 19 game with deep neural networks. The ground-breaking advance in computer Go brought artificial intelligence into public view and raised discussions on how to interact with machines in the future. However, AlphaGo is still a highly intelligent computer program without emotion and personality. This paper presents a novel game design of “Naughty AlphaGo”, which is an emotional Go robot player based on AI algorithm. Result shows that the emotion expression approach based on behavioral and kinematic characteristics can support human players’ perception about the AI player’s emotional states through interaction.
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