Modeling Believable Virtual Characters with Evolutionary Fuzzy Cognitive Maps in Interactive Storytelling

Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen

To generate believable virtual characters in real-time is a key issue to improve users' engaging experience in the interactive storytelling. In real life, the emotions and behaviors of characters evolve inductively according to the mutual causal relationships, with some stochastic variations. This is not addressed well in the virtual environment with conventional models, e.g. rule-based expert system, Fuzzy Cognitive Map and so on. In this paper, we use a computational model, namely Evolutionary Fuzzy Cognitive Map (E-FCM), to model the attributes of characters (such as emotions and behaviors) as concepts with the dynamic causal relationships among them. As an extension to FCM, E-FCM models not only the fuzzy causal relationships among the variables, but also the stochastic causal relationships, and asynchronous activity update of the concepts, so that the variables evolve in a dynamic manner with their respective evolving time schedules. As a result, the characters are presented with more realistic and dynamic emotions and behaviors, which enhances the user experience at last.

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